Marketing in messengers @ Chatfuel

I'm passionate about building products that solve real problems for real people, especially small businesses that power the everyday economy.

At Chatfuel, I lead product efforts to support service-based SMBs - salons, clinics, fitness studios, and beyond - helping them grow through automation, AI, and intuitive tools. We've built a mobile-first, end-to-end platform that streamlines everything from lead generation and booking to re-engagement and customer retention, all inside WhatsApp and Instagram DMs.

Our mission is to give 100M+ social-first service businesses the kind of operating system that Shopify gave to e-commerce: one that’s simple, powerful, and built for how they actually work today.

Previously, I’ve helped grow B2B and edtech products from the ground up to strong ARR, and driven improvements in monetization and retention at scale.

If you’re working on tools for service SMBs, AI adoption, or product-led growth, let’s connect!

Oleg Krasikov

Jira is becoming the fax machine of software development.

Here's what's happening at our company right now:

→ Our onboarding flow is 100% vibe coded
→ Most of our Coworker features are built with vibe code
→ We're shipping to production through AI agents

And when you work this way, Jira starts to feel absurd.

You spend more time filling out mandatory fields than it takes to actually ship the feature. The ticket has less context than a single prompt to an AI agent. The workflow was designed for a world where shipping took weeks, not minutes.

Creating a Jira ticket for something an AI agent can build and deploy in one session is like filing a travel request to walk across the hallway.

I think we're about to see a massive shift in dev tooling. The tools we rely on today like project management, ticketing, sprint planning were built for human-only teams moving at human speed.

AI agents don't need sprint ceremonies. They need context.

The next generation of dev tools won't ask you to fill out 15 fields. They'll understand what needs to be built and help you ship it.

Who else is feeling this friction?

CPO @ Chatfuel | Leading product for the AI-powered OS transforming service SMBs | Automate sales, booking & retention

We just shipped a small feature that makes a big difference. We taught Coworker how to handle backend errors.

In complex B2B SaaS products, dead ends are everywhere:
- Unsupported formats
- Broken integrations
- Invalid enums
- Unexpected data from third-party APIs

And when that happens, users get stuck. But not anymore.

Now, when Coworker hits a backend error, it:
1. Tries to automatically fix the issue
2. If it can’t, clearly explains what’s wrong
3. Suggests exactly how to resolve it

Real example 👇
- It fetched a pizza catalog
- Prices were in RUB
- Our enum doesn’t support that currency
- It attempted to resolve it automatically
- When that wasn’t possible, it suggested updating all prices to USD or MXN (since my account is set from Mexico country code) and even used the current live exchange rate from the Internet to guide the conversion.

No silent failures.
No “something went wrong.”
Just clear diagnosis + actionable next steps backed by real-world data.

Edge cases kill most complex systems. Chatfuel handles them before they become problems.

Co-founder and CEO at Bito. 

We build codebase intelligence for AI coding and reviews, so AI tools can reason about real systems instead of guessing. 

Before Bito, I built and scaled companies across multiple markets, including PubMatic (NASDAQ: PUBM). 

Right now, I spend most of my time thinking about AI, software systems, and why understanding codebases matters more than writing code faster.

Amar Goel

Your coding agent indexed your entire codebase and still has no idea how your services connect. Cursor, Claude Code, Copilot. 

They all build symbol tables, follow references, create searchable indexes when you connect your repos. Fast, accurate file lookup. And for scoped, single file edits, that genuinely works.

The problem shows up the moment work crosses service boundaries.

Your agent can find a file. It cannot tell you why a safeguard was added after a production incident, or which downstream consumers break if you change a schema. 

That knowledge lives in the relationships between code, and indexing does not capture relationships.

We keep seeing this pattern with teams of every size. 

They assume indexing solves the context problem, then spend weeks debugging agent output that looked right but missed the system entirely.

We wrote about why this keeps happening and what actually closes the gap.

Read here:

Bito | Top score on SWE-Bench Pro - Deep codebase intelligence for AI coding and reviews

Open article: Why Coding Agents Get Lost in Your Codebase (Even After Indexing Everything)  by bito.ai

Why Coding Agents Get Lost in Your Codebase (Even After Indexing Everything) 

taplio

The Battle

Oleg Krasikov

Amar Goel

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taplio

The Battle

Oleg Krasikov

Amar Goel

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Oleg Krasikov's LinkedIn Performance

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Performance ScoreOleg Krasikov's LinkedIn Performance