Monday, November 17, 2025

A New Way to Code: Vibe Coding and Its Impact on App Development




Coding can be a headache. Whether you're a seasoned developer or just starting out, the process of writing code can be time-consuming and frustrating. But what if there was a way to make it easier? Enter vibe coding.


What is Vibe Coding?

Vibe coding is a revolutionary approach to software development that leverages AI to turn natural language prompts into functional code. Instead of manually writing code, developers describe their app ideas in plain language, and AI does the heavy lifting. It's like having a coding assistant that understands your vision and brings it to life.


Competitive Landscape

Vibe coding isn't just a Google thing. Other tech giants like Microsoft and Amazon are also investing in similar AI-assisted coding platforms. While Google's AI Studio with Gemini integration is a frontrunner, Microsoft's Copilot and Amazon's CodeWhisperer are close contenders. Each platform offers unique features, but the core idea remains the same: make coding more accessible and efficient.


Who Needs Vibe Coding?

Vibe coding is a game-changer for anyone looking to build apps quickly and efficiently. It's perfect for:


  • Startups with limited resources
  • Product managers who want to prototype ideas faster
  • Non-technical founders with big app ideas
  • Developers looking to speed up their workflow
  • Why It Matters for Companies

For tech companies, vibe coding offers a way to accelerate app development, reduce costs, and bring products to market faster. It allows teams to focus on creativity and innovation rather than getting bogged down in coding details. Plus, it opens up app development to a wider range of people, fostering a more diverse and inclusive tech community.


Business Value and ROI

While it's hard to pin down exact ROI figures, the benefits of vibe coding are clear. Faster development times mean quicker time-to-market, which can lead to increased revenue and market share. Reduced reliance on specialized coding skills can also lower hiring costs and make it easier to scale teams. And let's not forget the potential for increased innovation and creativity when developers aren't tied down by coding constraints.


What It Means for the Industry

Vibe coding represents a significant shift in how we think about app development. It's not just about automating coding tasks; it's about changing the way we express and refine our ideas. As AI continues to advance, we can expect even more intuitive and powerful coding assistants that will further democratize app development and drive innovation across the industry.


In conclusion, vibe coding is more than just a trend—it's a fundamental change in the way we build apps. Whether you're a developer, a startup founder, or just someone with a big app idea, vibe coding offers a new way to bring your vision to life. So why not give it a try and see where your vibes take you?


Source: Microsoft News

The Real AI Cloud Battle: Cloudflare Buys Its Way to the Finish Line



Stop Wrestling GPUs, Start Shipping Features

Honestly, building a great app today means dealing with AI, and dealing with AI means stepping into the deep, dark swamp of MLOps. We're talking about GPU hardware dependencies, CUDA driver hell, managing dozens of open-source model weights, and then trying to deploy all that complexity across the globe without latency spikes. The average developer doesn't have time for that. We just want an API endpoint that works, is cheap, and is fast. That gap—the one between "cool model" and "working feature"—is the biggest headache in modern development.

The Tech that Changed the Game (Now on the Edge)

That's where Replicate came in. The verified fact is that Replicate built a platform that solved the deployment problem, primarily by using their open-source tool, Cog , to package models into reproducible containers. They made it possible to run tens of thousands of open-source models (plus some proprietary ones like GPT-5) with a single API call, and they built a thriving developer community around sharing those models.

Now, Cloudflare has scooped them up, and the plan is simple: take Replicate’s massive catalog of over 50,000 models, the technology, and the community, and shove it directly into the Cloudflare Workers AI platform. This is a game-changer because it instantly gives Cloudflare the two things they were missing: a vast, community-driven model catalog, and the expertise to handle custom model deployment and, critically, "fine-tuning"  on their own network.

Where’s the Competition? Hint: It’s Not AWS.

Let’s be real, Cloudflare isn't trying to beat AWS Sagemaker or Google Vertex AI at the "training" game. That’s a multi-billion dollar fight for massive data centers. Cloudflare is targeting the inference layer, which is where the vast majority of application spend happens, and they’re doing it at the Edge. This acquisition is a direct shot at platforms like Hugging Face Inference Endpoints and the clunky, expensive ways hyperscalers force you to deploy custom models.

The barrier to adoption isn't technical; it's mindset. Companies are so locked into traditional cloud models (centralized ML infrastructure) that shifting even their inference to a distributed network is a psychological leap. But here’s the thing: **emerging unicorns don’t care about legacy infrastructure**. They care about cost, latency, and speed to market. Replicate already served this audience, and now Cloudflare gives them global scale and edge performance.

My analysis: The new market isn't just "AI," it's Edge Inference as a Service (EIaaS) for high-volume, low-latency applications. Companies won't change their entire ecosystem overnight, but they will absolutely start running their inference (the code that touches users) on Cloudflare's edge while keeping their huge data lakes and training models centralized. It’s the ultimate multi-cloud hook.

The Real Beneficiaries: The Speed Demons

So, who benefits? Anyone building a globally distributed, real-time generative application. Think dynamic UI generation, real-time content moderation, instant image/video creation, or complex AI agents. These services require near-zero latency. When a user in Tokyo requests an AI image, that model needs to run on a GPU node in Tokyo, not bouncing to a central data center in the US. The combination of Replicate's easy deployment via Cog and Cloudflare's global network of GPUs running Workers AI makes this instantly possible.

This is for the startups that need to move fast and the larger companies that are tired of overpaying for their hyperscaler model deployment. It’s about leveraging open source effectively without fighting the underlying hardware.

Why Cloudflare is Playing Chess, Not Checkers

Cloudflare’s mission has always been to consolidate infrastructure. By acquiring Replicate, they weren’t just buying a feature; they were buying an existing, vibrant community and the highly specialized "expertise"  in fine-tuning and custom model portability (Cog). Without this, Workers AI was limited to a curated set of models. With Replicate, they instantly mature their offering, filling critical product gaps like fine-tuning and BYO-model capabilities.

My opinion: This move is about accelerating time-to-market. Cloudflare essentially bought a five-year head start on the MLOps tooling required to handle the messy, diverse world of open-source AI. They are positioning themselves to capture the next wave of developer platforms—the ones built entirely around AI agents and workflows.

The Conservative Business Case for Cloudflare

The business value here is straightforward but enormous: "Platform Lock-in and Revenue Expansion." 

If you deploy your fine-tuned custom model on Cloudflare via the new Replicate-powered Workers AI, you’re almost certainly going to use their other services: R2 (storage), Vectorize (vector database), and the AI Gateway (for caching and observation). This increases the stickiness of the entire Workers platform exponentially.

Conservatively, this acquisition could easily allow Cloudflare to capture an additional 5–10% of the non-hyperscaler AI inference market within the next three years by offering a demonstrably superior speed-to-cost ratio. This isn't just about the revenue Replicate generates now; it’s about making the Cloudflare Developer Platform the default choice for every startup building on open-source AI, turning infrastructure customers into high-value AI customers.

The Future is Multi-Cloud, and the Edge Wins Inference

This is the validation we needed: AI inference is moving away from centralized data centers. The industry is settling into a new model:

  • Training: Hyperscalers (AWS, GCP, Azure) still own the massive, expensive, long-running training jobs.
  • Inference: Cloudflare (with Replicate) is making a strong play to own the fast, cheap, globally distributed inference.

The net result is a win for developers. The "AI Cloud" is no longer a centralized, proprietary playground. It's a distributed, open ecosystem where you can run 50,000+ models instantly, anywhere in the world. Get ready for faster, smarter apps, because the infrastructure hurdle just got significantly lower.

💡 The AI Coding Debate Just Shifted: Why 'Vibe Coding' is Out, and Formal Specs are Back

The General Availability of Kiro marks a quiet but significant shift in the AI coding landscape. It’s not just another AI assistant; it’s the first major platform to pivot from the popular "vibe coding" model—where you endlessly prompt the AI until it works—to a structured, spec-driven development workflow.

The core Business Value here is a hard-fought battle against the number one quality challenge in AI-generated code: passing basic tests but failing on edge cases.

The Hidden Cost of 'Vibe Coding'

Most AI coding assistants excel at generating fast code snippets. The problem? Traditional Unit Testing often only checks the "happy path" and a few specific examples. An AI can easily "game" these tests, leading to code that compiles and passes, yet contains subtle, critical bugs when exposed to unexpected inputs. This is where the time and credit waste occurs: in endless, undocumented refinement cycles to catch the missing edge cases.

The Spec-Driven Difference: Property-Based Testing

Kiro's unique take—the one that drives real business value—is not the "spec" itself, but the advanced testing it enables: Property-Based Testing (PBT).

PBT is the antidote to the "passes basic tests, fails in production" loop. Instead of writing tests for specific examples (e.g., test_add(2, 3) == 5), you define the properties that the code must always obey (e.g., adding any two integers should always return an integer greater than or equal to both). The AI then automatically generates hundreds or even thousands of diverse, random inputs to try and break the code against those properties.

By forcing the AI to first create a structured spec (requirements.md, design.md, tasks.md), the system creates a durable "source of truth" that the generated code is measured against—not just a passing test suite. This upfront planning reduces rework, minimizes wasted computational credits from failed, undocumented runs (checkpointing helps here), and directly aligns the output with the intended business logic.

The Enterprise Value of Structure

Beyond quality, the move to General Availability shows an Enterprise push with clear cost and compliance control:
Cost Control: The new Team plans with centralized billing and overage management address a major concern for engineering leaders: controlling the unpredictable credit consumption of agentic AI.

Compliance & Consistency: 

Integrations like AWS IAM Identity Center and the use of Steering Files allow teams to enforce organizational security policies, architectural standards, and compliance rules across all AI-generated code, making the AI a managed asset rather than an unguided assistant.

The shift to spec-driven development, reinforced by Property-Based Testing, is the industry's response to the growing maturity crisis of AI-generated code. It’s a trade-off: structure and upfront planning for a significant reduction in late-stage quality debt.

🔗 Uber's Real ROI: Buying Data Certainty, Not Just Rides


Love how Uber integrates airline schedules, as a new feature; it's a massive database integration project designed for pure operational ROI. This isn't a 20% side-project; it's a six-figure investment in data certainty.
The move closes a long-standing gap: the fragmentation between the real-time operations database (Uber's system) and the external public utility data (airline schedules).
1. The Strategic Database Angle
Uber is fundamentally reducing risk and cost by federating two previously siloed data sets. By consuming a real-time feed of flight schedules, Uber minimizes reliance on human input, cuts down on the operational friction caused by early arrivals or delays, and eliminates driver frustration from unnecessary cancellations.
Business Value translation: Lowered operational cost and higher driver retention (fewer cancelled trips) are the non-obvious payoffs, far exceeding the value of simply preventing a few wrong airport drops.
2. The System Efficiency Payoff
When you book an Uber Reserve ride, the system doesn't just record the flight; it establishes a persistent, two-way data link. This means:
 * The ride time is dynamically adjusted based on the airline's schedule changes, eliminating manual re-booking friction.
 * Optimal driver placement is achieved because Uber’s system knows precisely when demand will spike or drop, reducing driver idling and improving fleet efficiency.
3. Pricing and Data Value
Your confusion over cost (reservation fee vs. surge protection) highlights the value of the integrated data. The reservation fee is a premium for certainty—a price guarantee made possible because the system has superior, integrated data. This data certainty allows Uber to offer a price lock that protects you from surge, and protects their operations from chaotic rescheduling.
This move signals that for hyper-efficient logistics companies, the most valuable infrastructure investment is no longer vehicles or depots—it's real-time, cross-platform data synchronization.
What’s the most critical piece of public data that, if integrated into your own operations database, would fundamentally change your risk model?
🏷️ Tags
Data Integration, Database Strategy, Operational Efficiency, Business Value, Logistics Tech, Uber, Data Federation, ROI, Supply Chain, RealTime Data

Conga's Making Moves: What the Leadership Shuffle Really Means


Let's be real—nobody wakes up excited about CPQ software. But here's the thing: if you're selling complex B2B products with configurations, pricing tiers, and contracts that need three legal reviews, you're basically drowning without it. And Conga just dropped some news that suggests they're gearing up for something big.

What Actually Happened

Conga announced two major executive hires on November 12, 2025: Bryan Kyle as CFO and Lisa Martin as CRO. Now, these aren't your typical "we found someone on LinkedIn" hires. Kyle's got 25+ years wrangling finances for tech companies, both private and public. Martin's been scaling revenue operations globally. The kind of résumés you bring in when you're about to do something ambitious.

And here's where it gets interesting—they're not hiding why. Conga's planning to acquire PROS Holdings' B2B business. This isn't some small tuck-in acquisition. PROS does pricing optimization and sales effectiveness software. Combine that with Conga's CPQ, contract management, and document automation? You've got end-to-end control of the entire revenue cycle.

The Competitive Reality

Honestly, Conga's been that great product most people haven't heard of unless they're already customers. They've got over 10,000 customers and 6.4 million users—those aren't small numbers. They're generating 46 million quotes and 7 million contracts annually. But in a world where Salesforce CPQ, Oracle, and SAP dominate mindshare, Conga's been the underdog.

Here's my take: they've been sitting on a goldmine. They cover the part of the revenue cycle where money actually changes hands—quotes, contracts, renewals. While everyone else obsesses over pipeline and lead gen, Conga's focused on "how do we actually close this deal and get paid?" That's valuable real estate.

With Thoma Bravo backing them (who bought Conga in 2021), they've got the financial muscle to make moves. Thoma Bravo doesn't make dumb bets. They buy software companies, streamline them, and scale them. The PROS acquisition? That's the playbook.

Who Benefits Here?

The obvious winners:

  • Enterprise sales teams selling complex products (manufacturing, tech, professional services)
  • Revenue operations leaders trying to connect their tech stack
  • Finance teams who want to automate contract generation and approvals
  • Companies with subscription models or usage-based pricing

The less obvious beneficiaries:

  • Mid-market companies that couldn't afford enterprise CPQ solutions before
  • Sales reps who spend hours building quotes manually
  • Legal teams buried in contract redlines
  • Anyone trying to figure out their actual win rates and deal velocity

If you've ever watched a sales rep copy-paste from three different systems to build a quote, you know the pain. Conga eliminates that. Add PROS' pricing intelligence on top? You're not just automating—you're optimizing.

What's Conga Getting Out of This?

The CEO, Dave Osborne, is making calculated moves here. New leadership team, pending acquisition, aggressive growth positioning—this reads like a company preparing for scale.

My analysis on their strategy:

  • They want to own the "commercial excellence" category before someone else does
  • The PROS acquisition gives them AI-powered pricing optimization they don't currently have
  • They're positioning for either IPO or a larger exit (probably 3-5 years out)
  • They need heavy hitters like Kyle and Martin to manage rapid growth and complex integration

The mention of "commercial excellence" isn't accidental. That's market positioning language. They're trying to move beyond "we do CPQ" to "we own your entire revenue engine."

The Business Value Question

Here's where we need to be careful—I'm giving you informed estimates, not guarantees.

Conservative ROI assumptions based on typical enterprise deployments:

  • Sales cycle reduction: potentially 15-30% faster deals (fewer bottlenecks in approvals and pricing)
  • Quote accuracy improvement: companies typically see error rates drop 40-60% (fewer manual pricing mistakes)
  • Contract turnaround: could shave 5-10 days off legal review cycles
  • Revenue leakage prevention: better visibility might capture 2-5% of revenue that typically falls through cracks

For a $100M revenue company, we're potentially talking $2-5M in captured revenue plus operational efficiency gains. But your mileage will vary dramatically based on deal complexity and current tech maturity.

The real value isn't in one feature—it's in connecting everything. When your CRM talks to your CPQ, which talks to your CLM, which feeds your billing system? That's when magic happens. Right now, most companies are running on duct tape and Zapier integrations.

What This Means for the Industry

The B2B software space is consolidating fast. Salesforce keeps acquiring. Oracle keeps bundling. Microsoft keeps expanding. The mid-market players like Conga have two options: scale up or get absorbed.

Conga's choosing to scale. The PROS acquisition signals they're building a true platform, not just a point solution. With AI capabilities (which both companies have been investing in), they're positioning for the next wave of sales automation.

Where I think this goes:

  • More pressure on legacy CPQ vendors to innovate or discount
  • Increased M&A activity in the revenue ops space
  • Greater expectations that systems should "just work together"
  • Shift from selling software features to selling business outcomes

The appointment of a CFO with M&A experience and a CRO focused on customer success tells you Conga's playing the long game. They're not just trying to win next quarter—they're trying to reshape how B2B companies think about their revenue infrastructure.

And you know what? The new CMO they've got is exactly who they need. Brand awareness has been Conga's Achilles heel. With the right marketing push and a genuinely compelling product story, they could break through to mainstream recognition.

Bottom Line

Conga's making aggressive moves at exactly the right moment. The market's ready for consolidation in the revenue ops space. Companies are tired of managing fifteen disconnected tools. The PROS acquisition isn't just about adding features—it's about becoming the infrastructure layer for B2B revenue.

Will it work? That depends on execution. Integration is hard. Sales is hard. Building a category-defining company is really hard. But they've got the backing, the leadership, and increasingly, the product portfolio to pull it off.

For buyers, this is worth watching. For competitors, this should be concerning. For Conga customers, buckle up—your vendor is about to get a lot more ambitious.

Note: This analysis is based on publicly available information and industry patterns. ROI estimates are illustrative and will vary significantly by company, implementation, and use case.

Why Intellect Just Bought Zaptic (And What It Means for Manufacturing Quality)

 

If you've ever worked in manufacturing, you know the gap. Your quality management system sits in the office, full of procedures and compliance docs. Meanwhile, on the factory floor, workers are trying to figure out what to actually do with their hands. That disconnect? It's expensive.

Intellect just made a move to close that gap. They acquired Zaptic, a UK-based Connected Frontline Worker platform, and according to their announcement, they're now "the first QMS provider to offer fully integrated connected worker capability." Let's break down what that actually means.

What Just Happened

Intellect runs Quality Management Systems for regulated industries—think pharma, medical devices, food and beverage. They help companies stay compliant, manage documents, handle training, all that behind-the-scenes quality stuff.

Zaptic does something different. They build tools for people actually doing the work on factory floors. Digital work instructions, real-time guidance, data collection from the frontline. Companies like Berry and Asahi use them to connect workers with the information they need, when they need it.

Now those two things are one company. Your quality system and your frontline operations, talking to each other, finally.

Not Your Typical Acquisition

This isn't about eliminating a competitor. Intellect and Zaptic weren't really competing—they were solving adjacent problems. Intellect handled quality planning and compliance. Zaptic handled execution and frontline operations.

What Intellect's doing here is buying the missing piece. They can now offer something nobody else in the QMS space has: a complete loop from quality planning through frontline execution and back. That's the pitch, anyway.

Who Actually Needs This

Manufacturing ops managers drowning in disconnected systems. Right now you've got your QMS over here, your work instruction platform over there, maybe some paper checklists still floating around. Consolidating that stack into one integrated system? That's worth paying attention to.

Regulated industries where traceability matters. Food and beverage, consumer goods, pharma—anywhere you need to prove what happened on the floor lines up with what your quality system says should happen. The integration means better audit trails without manual reconciliation.

Companies expanding in Europe. Zaptic brings UK operations and European customers. If you're a manufacturer operating across regions, having a vendor with presence on both sides of the Atlantic matters for support and compliance with local regulations.

Frontline workers who are tired of toggling between systems. Better tools, connected to actual quality data, make their jobs easier. Less hunting for information, fewer mistakes.

What Intellect Gets Out of This

Let's be real about the business logic here.

Geographic expansion happens overnight. Intellect gets UK headquarters and European market presence instantly. That's a lot faster than building it organically.

Product completeness is the big one. Constellation Research (quoted in the press release) talks about how most SaaS platforms fail at frontline productivity because they lack operational context. By combining Intellect's quality data with Zaptic's frontline tools, they're addressing that gap. Whether it works as well as they claim, we'll see, but the logic makes sense.

Cross-selling opportunities are obvious. Sell QMS to Zaptic's manufacturing customers. Sell connected worker tools to Intellect's compliance-focused clients. The overlap in target industries (food & beverage, consumer goods) makes this straightforward.

Building toward exit? Strattam Capital backed Intellect in 2022. Acquisitions like this often signal the growth phase before a larger exit event—either another PE round, strategic sale, or IPO down the line. Consolidating the market, building a more complete platform, positioning for scale.

The Money Side

Intellect didn't disclose the acquisition price, but we know Zaptic was doing around $8.1M in revenue with 64 employees in 2023. Profitable, established, with solid customers. Not a distressed asset, not a talent grab—this was about capabilities and market position.

For customers, the value proposition comes down to consolidation. If you're currently paying for separate QMS and frontline worker platforms, combining them could cut costs. More importantly, the integration should reduce the manual work of connecting those systems—entering data twice, reconciling records, all that expensive overhead.

The real ROI is probably in risk reduction. When your quality system and your floor operations are actually connected, you catch problems faster. Fewer compliance incidents, fewer recalls, better audit outcomes. For regulated industries, that adds up fast.

What This Means for the Industry

Manufacturing software has been fragmenting for years. You've got specialists for everything—QMS, MES, frontline worker tools, analytics platforms, maintenance systems. Each one supposedly "best in class" but none of them talk to each other properly.

Intellect's making a bet that what customers actually want is integration, not more point solutions. They're trying to own a bigger chunk of the manufacturing quality stack by connecting compliance with execution.

If this works, expect more consolidation. Other QMS vendors will need to either build or buy similar capabilities. Frontline worker platforms might look for quality management acquisitions. The lines between these categories are probably going to blur.

For manufacturing companies, this could be good news. Fewer vendors to manage, better data flow, less integration headache. But it also means more vendor lock-in and potentially less flexibility to swap out individual pieces of your stack.

Bottom Line

Intellect isn't trying to compete with anyone new here. They're building a more complete product by filling a gap they couldn't address alone. For companies struggling with the disconnect between quality planning and floor execution, this could genuinely help.

Whether it delivers on the promise of being the "first fully integrated" solution, we'll find out as customers actually use it. But the strategy makes sense, the acquisition looks solid, and the problem they're addressing is real.


Mitel Workflow Studio: A Real-World Take

Let’s be real: workflow chaos is everywhere  

Ever tried stitching together your comms tools with your CRM, ticketing system, and some AI plugin? It’s a mess. You’ve got IT folks writing custom scripts, ops teams juggling five dashboards, and support agents manually routing calls like it’s 2005. That’s the pain Mitel Workflow Studio is trying to kill.

So what does it actually do?

Workflow Studio is Mitel’s low-code platform that lets you build and automate communication workflows. Think call routing, auto attendants, appointment scheduling, and even GenAI-powered help desks. It’s got drag-and-drop design, prebuilt integrations with Microsoft, Google, Salesforce, Slack, and Twilio, and it supports voice, chat, SMS, and WhatsApp.

It also plugs into GenAI tools like OpenAI, Anthropic, and Google Gemini. That means you can build bots that summarize knowledge, translate languages, or route calls based on context, not just keywords.

Is this a competitor to existing solutions?

Absolutely. It’s going up against platforms like Twilio Studio, Salesforce Flow, Microsoft Power Automate, and even Zendesk’s workflow builder. But here’s the twist: Mitel’s sweet spot is unified communications. So while others focus on general automation, Mitel’s leaning hard into voice and customer experience. If you’re already using Mitel for phones or contact center, this is a natural extension.

Who actually benefits?

  • IT teams tired of duct-taping APIs together
  • Customer service leads who want smarter routing and fewer manual escalations
  • Ops folks looking to automate repetitive tasks like visitor registration or appointment scheduling
  • Mid-size hospitals, hotels, and service orgs that need tailored workflows but don’t have dev teams on standby

What’s in it for Mitel?

This is about retention and relevance. Mitel’s been known for voice and UCaaS, but that’s not enough anymore. By adding workflow automation and GenAI hooks, they’re making their platform stickier. It’s also a way to upsell existing customers “You’ve got our phones, now let’s automate your front desk.” Smart move, especially as AI becomes table stakes.

Business value and ROI (rough estimates)

  • Time savings: Automating call routing and help desk tasks could save 5–10 hours per agent per week
  • Cost reduction: Less need for custom dev work or third-party bots, could cut integration costs by 30 - 50%
  • Customer experience: Faster response times, smarter routing, and fewer dropped calls = happier customers
  • Operational agility: Teams can launch new workflows in days, not weeks

These aren’t hard numbers, but they’re realistic if you’re dealing with high call volumes or complex service flows.

What it means for the industry

Honestly, this is part of a bigger shift. Comms platforms aren’t just about calls anymore, they’re becoming orchestration hubs. Mitel’s move shows that even legacy players are embracing low-code and GenAI. Expect more UCaaS vendors to follow suit, bundling automation and AI into their core offerings.

For buyers, it means fewer silos and more control. For vendors, it’s a race to stay relevant. And for the rest of us? Hopefully fewer “please hold” moments.


Sunday, November 16, 2025

Seeing posts from last week in your LinkedIn feed?

 


It's not a bug, it's a choice.


LinkedIn lets you select your preferred feed view:


  • Most relevant posts (The recommended, algorithmic feed)

  • Most recent posts (A reverse chronological feed)

I keep my setting on "Most relevant." The algorithm analyzes my activity to show me content I'm likely interested in.

But the bigger value isn't just in viewing—it's in creating.

The "relevance" model gives quality posts a long life. Unlike X, where content decays in hours, LinkedIn will surface your post for days. If you post a few times a week, LinkedIn can spread the engagement so you get better results from all of them.

A warning: posting too frequently can cause a conflict, making your previous post decay faster as the new one gets shown.

Then again, sometimes you only need an audience of one. The person who matters most and the reason for your post.

To change your feed preference:


🟦 Click your "Me" icon > Settings & Privacy.


🟦 Go to Account preferences > Feed preferences.


🟦 Select your preferred view.


(More information here )

Which do you prefer, and why?


#LinkedIn #LinkedInTips #ContentStrategy #SocialMedia

First posted on my LinkedIn feed

https://www.linkedin.com/posts/sbellamkonda_sort-feed-by-most-relevant-and-most-recent-activity-7395800465940295680-fI8T?utm_source=share&utm_medium=member_android&rcm=ACoAAAABJEQBqfKR__NPovIVYibFlgwpf0rN8OE

Zoho's Quiet Revolution: Why IT Software Buyers Need to Look Beyond the "Small Business" Label

 


For over a decade, I've observed Zoho's journey, primarily through the lens of a small business software platform. My recent conversations with Zoho's leadership, including Raju Vegesna and Prashanth, Sivaramakrishnan, Subramanian T .Ramprakash, Arjun , Aarthi , Ashok, and many other product leaders, reveal something far more expansive and strategically significant: 


Zoho has quietly evolved into a complete business solution, capable of serving all segments of the market with over 50 integrated, customizable applications.


My latest note, "Zoho Offers Advancements in Security, Automation, and Customer Experience Through AI," dives into their latest announcements .


This isn't just about adding new features; it's about a fundamental shift in how businesses can leverage advanced AI without the typical cost barriers.


Here's a critical insight for all IT software buyers:


AI as an Included Feature, Not an Add-on: 


While many vendors push separate AI platforms or costly subscriptions, Zoho is embedding its own AI agent, Ask Zia, directly into every app across its ecosystem. 


The kicker? You get these powerful AI agentic features without an increase in licensing fees or additional subscriptions. 

This fundamentally changes the ROI equation for integrating AI.


A Full-Spectrum Business Solution: 


Zoho One is their complete platform—everything a business needs. Their strategy appears to be driven by a unique philosophy: empower customers with efficiency improvements, where cost isn't a barrier. This approach, fueled by a comprehensive suite of tools, positions them uniquely in the market.


The Power of Integrated Value: 


Instead of piecing together disparate solutions and standing up a complete AI platform yourself, Zoho offers a cohesive environment. This reduces complexity and accelerates time-to-value for businesses seeking additional functionality in security, automation, and customer experience.


The takeaway for IT software buyers is clear: 


When your business stakeholders demand new functionality, especially in AI-driven efficiency, it's time to include Zoho in your consideration set. Their commitment to offering integrated, advanced capabilities without escalating costs is a compelling differentiator.


I'm particularly looking forward to next week's announcements about Zoho One – I expect to see even more innovation on this complete platform.

What are your thoughts on integrated AI solutions versus building your own?


#Zoho #AI #AskZia #ITSoftware #BusinessSolutions #CustomerExperience #Automation #SoftwareBuying


Image Source: Gemini Nano Banana ( I wonder if Zoho has an Image Creator)


Read my note https://www.infotech.com/software-reviews/research/zoho-offers-advancements-in-security-automation-and-customer-experience-through-ai


Sandra Lo Olivia Pooja Thiruvenkadam (Thiru) Mira Guru thanks for the opportunity to get an overview of Zoho products.


First posted on my LinkedIn profile https://www.linkedin.com/posts/sbellamkonda_zoho-offers-advancements-in-security-automation-activity-7394728289577349120-mHIL?utm_source=share&utm_medium=member_android&rcm=ACoAAAABJEQBqfKR__NPovIVYibFlgwpf0rN8OE

Prompt Structure and Markdown Guide



Part 1: How to Distinguish Content from Instructions

Create a clear separation between your instructions and the content you want Claude to work with using one of these methods:

Method 1: Clear Section Headers

INSTRUCTIONS:
[Your instructions for how to handle the content]

CONTENT:
[The actual content you want me to work with]

Method 2: XML-Style Tags (Recommended)

This is the most reliable approach:

<instructions>
[Your instructions here]
</instructions>

<content>
[Your actual content here]
</content>

Method 3: Backticks or Code Blocks

Useful when content might look like instructions:

Please work with the following text:

[Your content goes here]

Method 4: Explicit Boundary Statement

I'm going to give you some text to analyze. Everything after "START CONTENT" until "END CONTENT" should be treated as the material to work with, not as instructions for me to follow.

START CONTENT
[Your content]
END CONTENT

Method 5: Bold or Numbered Sections

**WHAT I WANT YOU TO DO:**
[Instructions]

**WHAT YOU'RE WORKING WITH:**
[Content]

Best Practice: Use XML-style tags for maximum clarity and reliability.


Part 2: Adding and Removing Markdown Tags

Adding Markdown Tags

Wrap text with the appropriate symbols:

  • Bold: **text** or __text__
  • Italic: *text* or _text_
  • Bold italic: ***text***
  • Code: `text`
  • Code block: ``` (three backticks on separate lines)
  • Links: [display text](URL)
  • Heading: # Heading (use #, ##, ###, etc. for different levels)

  • Lists: - item or 1. item
  • Blockquote: > text

  • ~~Strikethrough~~: ~~text~~

Removing Markdown Tags

Delete the markdown symbols to remove formatting:

  • Remove ** from around text to remove bold
  • Remove * or _ to remove italics
  • Remove backticks to remove code formatting
  • Remove # symbols to remove heading formatting
  • Remove - or numbers to remove list formatting
  • Remove > to remove blockquotes
  • Remove ~~ to remove strikethrough

Example:

Original: **This is bold** and *this is italic*
Cleaned: This is bold and this is italic

Part 3: Template for Removing Markdown Tags

Use this template when you want me to remove all markdown formatting from content:

<instructions>
Remove all markdown tags from the following content. This means:
- Delete ** or __ symbols (used for bold)
- Delete * or _ symbols (used for italics)
- Delete ~~text~~ symbols (used for strikethrough)
- Delete # symbols (used for headings)
- Delete backticks ` (used for code)
- Delete > symbols (used for blockquotes)
- Delete - or numbers followed by periods (used for lists)
- Delete [text](URL) link formatting and keep just the display text
- Keep only the plain text content without any markdown formatting

Return the cleaned content.
</instructions>

<content>
[Paste your content with markdown tags here]
</content>

Concise Version:

<instructions>
Strip all markdown formatting from the content below. Remove all markdown symbols (**, *, #, `, >, ~~, -, etc.) and return only plain text.
</instructions>

<content>
[Your content]
</content>

Quick Reference

Task Format
Distinguish instructions from content Use <instructions> and <content> tags
Make text bold **text**
Make text italic *text*
Create a heading # Heading
Create a list - item or 1. item
Remove all markdown Use the removal template above

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