How we work
Not human vs AI. Not AI replaces human. This is human + AI—senior experience guiding AI capability. Each doing what they're best at.
Core beliefs
Principles learned through a year of trial and error. Mostly error.
Plan First, Then Build
Every task starts with a plan. AI proposes, human approves. We iterate until the approach makes sense—then we execute. No coding before alignment.
Verify Everything
AI generates code. Humans review every line—like pair programming with a talented junior. Trust but verify. Always. No exceptions.
PR, Never Push
AI creates pull requests. Humans review and merge. Direct pushes to main are forbidden. This is non-negotiable.
Document Failures
When AI makes mistakes, we document them. Institutional memory beats repeated errors. Every failure becomes a guard rail.
Small Context, Big Results
Don't dump entire codebases into context. Be surgical. One file, one problem, one solution. Focused context produces better output.
AI Handles the Boring Stuff
Tests. Docs. Configs. Migrations. Boilerplate. Let AI handle tedious work so humans can focus on architecture and hard problems.
The workflow
Every feature, every bug fix, every change follows this process.
Issue Tracking
Every task lives in Linear or GitHub Issues. Specs, acceptance criteria, context. No work starts without a ticket.
We work like a large team—because we are one. Structure enables speed.
Planning Phase
AI proposes implementation approach. Human reviews, asks questions, refines. We iterate until we're aligned.
This is where senior experience matters. Bad plans become expensive bugs.
Implementation
AI writes code, creates tests, updates docs. Human reviews diffs in real-time. Line by line.
Think pair programming, not magic wand. The human is always present.
Testing
Unit tests, integration tests, E2E tests. All run automatically on every build and deploy.
No green, no ship. Testing isn't optional—it's how we verify AI output.
Review & Merge
PR submitted. Human does final review. CI must pass. Only then: merge to main.
The gate that keeps production safe. Every change earns its way in.
Documentation
Code changes trigger doc updates. Architecture decisions recorded. Nothing lives only in chat.
Chat disappears. Docs survive. Everything important gets written down.
Tech stack
AI Models
Languages
Frontend
Mobile
Backend
Database
AI Tools
Testing
Infra
CMS
Monitoring
Workflow
Honest truths
What we've learned that the hype cycle won't tell you.
AI won't make you 10x productive overnight. Anyone who says otherwise is selling something.
Setup is 10x faster with AI. Actual coding is maybe 2-3x. That's still huge.
80% of code gets rewritten anyway. Ship the right solution, not "perfect" code.
Senior devs win at AI coding—not because of better prompts, but because they know what good looks like.
The real unlock isn't the tool—it's understanding what it's good at and ruthlessly applying it there.
Why this works
The real winners of AI-augmented development are senior developers. Not because we write better prompts—because we understand what good code looks like.
We know how to architect systems that scale. We know where the edge cases hide. We know which shortcuts become expensive debt.
AI handles velocity. Humans handle judgment. Together, you get both—without sacrificing either.
Proactive monitoring
We don't wait for things to break. Our agents watch your systems around the clock—and fix problems before your users notice.
Most teams find bugs when users report them. We find them at 3 AM—before they become incidents.
Our AI agents have read-only access to your logs, error trackers and performance metrics. They run continuous analysis: spotting anomalies, degradation patterns and silent failures that humans miss.
When something looks wrong, you get a detailed report with root cause analysis and a proposed fix—not just an alert. We go from "something's off" to "here's what happened, here's the fix, here's the PR" in minutes.
This isn't theoretical. We run this on our own ventures 24/7. Every morning we wake up to a report of what was caught and resolved overnight.
This is how Vigil was born — our own infrastructure agent, now available as a managed service. vigil.kerber.ai
Continuous log analysis
AI agents monitor Sentry, Datadog, CloudWatch and custom logs. Pattern matching catches issues that static alerts miss—like gradual memory leaks or slowly increasing error rates.
Overnight autonomous fixes
Critical bugs found at 2 AM get a PR by 6 AM. Non-critical issues get documented and prioritized. You wake up to solutions, not surprises.
Trend detection & forecasting
We don't just watch for fires—we predict them. Usage patterns, infrastructure costs, API deprecations. You get ahead of problems instead of reacting to them.
But who takes over when seniors move on?
The right question. Here's our answer.
"Senior devs win at AI coding because they know what good looks like." True, but what happens when that senior leaves?
This is exactly why expertise-as-a-service works. Companies don't need to retain expensive seniors full-time—they rent the judgment. 1-2 hours per week of senior guidance, not 40 hours of babysitting.
And we don't just review code. We build quality systems that outlive the project: documented patterns, architectural decision records and test suites that codify "what good looks like."
The goal isn't seniors reviewing AI forever. The goal is senior knowledge becoming sustainable.
Expertise on demand
Senior oversight without senior salaries. One expert can guide multiple projects—you get the judgment without the headcount.
Knowledge that persists
Every review becomes documentation. Every decision gets recorded. When we leave, the quality systems stay.
Faster learning loops
Juniors working with AI get real-time feedback. The 2027 junior will have seen more patterns than a 2017 senior. We accelerate that.
Want this for your team
We help companies set up AI-augmented workflows that actually work. It's not about the tools—it's about the system around them.
Book a consultation