Beyond coding agents

The software factory is real, but building one alone is brutally hard.

You've probably seen it by now: agents can carry a serious share of software delivery. The hard part is turning that into a system your whole team runs every day. That's the part we do with you. We bring the blueprints and the training, build the factory with your team on your own repos, and leave when your people run it without us.

Take the free maturity quiz See the Factory Accelerator

Three minutes, eight questions. You get your team's level and a peer benchmark by email.

Engineering leaders at Valant, SQUR, and ITB Consulting trust us with their teams. You may have heard Juri on the Fraunhofer IEM Tech Talk or the AI Agents Podcast.

Sound familiar?

You can see AI moving the needle, but you can't steer it yet.

A couple of your devs get remarkable results with agents, while most of the team still uses AI like fancy autocomplete.
Every developer works with it their own way, so the quality of what ships depends on who wrote it.
You see movement in the numbers, but you can't say what's driving it or which part to scale.
And the setups that actually work live on personal laptops. When that developer leaves, the setup leaves with them.

None of this means your team is doing badly. It means the tools arrived faster than the way of working. That gap has a fix, and the numbers below show why it's worth closing.

You can see AI moving the needle, but you can't steer it yet.

What 2026 actually looks like

90%

of developers regularly use an AI tool at work

JetBrains AI Pulse, January 2026, 10,000+ developers

64%

of teams report 25%+ velocity gains from AI. The gains are real.

Jellyfish, State of Engineering Management 2026

+60%

more PRs merged per week by daily AI users vs non-users (2.3 vs 1.4)

DX, Q4 2025 Impact Report

10%

of orgs pair high adoption with strong enablement. Everyone else runs on individual effort.

Jellyfish, State of Engineering Management 2026

Where we come in

The two problems CTOs call us about.

Usually it's one of them. Sometimes it's both.

Problem one

A few of your devs are flying, and the rest never took off.

Two or three developers ship like never before. The rest tried the tools, got burned once, and quietly went back to typing everything by hand. Your seniors still call the whole thing autocomplete.

We train the whole team on your own codebase, seniors and skeptics included, until working with agents is simply how they work. Person by person, because a mandate from above has never converted a skeptic.

Book a call

Problem two

The gains are real, but the process is anyone's guess.

Give two devs the same task and the same model, and one needs five minutes while the other needs forty. There are ten private workflows where there should be one shared process, and you're tracking seats instead of outcomes.

We take what your best developers already figured out and make it the whole team's way of working: written down, versioned in your repos, behind one set of quality gates. Then we baseline and measure it, so you finally know what to scale.

Book a call

Not sure which one describes your team? The three-minute maturity quiz will tell you.

The fix

One machine that runs your software delivery, end to end.

Plan, build, test, review, ship. In a software factory, agents run that loop behind your quality gates, while your engineers feed it intent and judge what comes out. Every fix becomes a rule, so the same mistake doesn't come back twice.

Why does this matter? Because agentic coding in the IDE only speeds up the middle of your process, and a faster middle squeezes both ends. Reviews pile up, product can't feed stories fast enough, and quality starts to slip. The factory runs the whole line as one flow, so the speed actually reaches production.

Your engineers stay in charge the whole way. They set the direction, tune the guardrails, and decide what ships. We make your seniors the architects of the factory, not its victims.

You feed intent, and judge the outcomes

1 Plan Intent to scoped work

2 Build Agents write the code

3 Test Checks run on the line

4 Review Behind your gates

5 Ship Merged and deployed

One loop, run end to end

Quality gates between every stage

Who you'll work with

Juri Kuehn

Hi, I'm Juri. I've been building software for over 30 years, and these days I build it with AI agents every single day, in production. Somewhere past 5,000 hours of it by now.

That daily work is where our method comes from. I join engineering teams, set them up for agentic work, and ship with them on their own code until the new way of working sticks. Codeligence grew out of exactly that.

30+: Years in software
12+: Teams shipped
Daily: Production code with agents

"AI requires a new mindset and new workflows. Letting go of old habits and accumulated knowledge is not always easy. I take it to heart to make the transition as smooth as possible and show a bright perspective on using AI in the new software development era."

What the people we've worked with say.

Real names, real companies. Happy to introduce you if you want to hear it firsthand.

"We were using Claude Code but treating each session as a one-off, with no shared conventions across the team. Now we approach it as an orchestration model, not a coding assistant. The goal shifted from AI helps us code faster to AI handles implementation while we supervise architecture and outcomes."

Bryan Scown

Director of Software Engineering, Valant

"We save hours each sprint with dependable story refinements and test plans, without adding complexity to our workflow. Codeligence has been reliable and easy to work with."

Adam Lundqvist

CEO, SQUR

"Working with Codeligence was completely uncomplicated. We were able to evaluate and start using AI technology quickly and with minimal effort. Getting started was effortless."

Tobias D. Kern

Managing Director, Atelier für Mediengestaltung

Who this is for

Engineering leaders who want the new way of working to stick.

We're not here to lecture converts or to argue with skeptics. We do our best work with leaders whose teams already have the tools, but haven't turned them into a shared way of working yet. That's probably you if:

✓
You lead a team of 5 to 30 developers.
✓
Your devs have the AI tools, but most still use them like autocomplete.
✓
Someone on your team is ready to own adoption and keep pushing after we leave.
✓
You report on velocity and quality, so you want a configured repo, not a pep talk.
✓
Your stack is TypeScript, Python, Java, C#, Go or similar. Greenfield or a ten-year-old codebase, both work.

The roadmap

Six levels of AI-assisted engineering.

AI-assisted development has levels, the same way driving automation does. Most teams sit around level 2 without knowing it. Finding out where you are is the useful first step, because the levels build on each other and skipping ahead doesn't work.

Manual coding

You write everything yourself.

Human oversight

100%

Conversational prompting

Copy and paste from a chat window.

Human oversight

~95%

Inline suggestions

Most teams are here

Autocomplete finishes your lines. This is where most teams sit today.

Human oversight

~80%

Contextual pair programmer

The AI sees your whole repo and works with you in the IDE.

Human oversight

~65%

Agentic engineering

A scoped ticket goes in, a reviewed PR comes out. The measured gains start here.

Human oversight

~50%

Your Software Factory

We take you here

Your team writes specs and judges outcomes, and the factory does the rest.

Human oversight

<20%

Two things we tell every team

You can't skip levels.

Each level builds on the discipline of the one before it: coding standards, CI, review culture, test coverage. Put level 4 tooling on a level 1 codebase and you get expensive chaos.

Each level up is more about people than tech.

Level 1 needs a legal sign-off. Level 3 needs shared standards. Level 5 needs new roles and new habits. The technical work shrinks with every level, and the organizational work grows.

How it works

From first call to a team that ships differently.

You won't find a package list or a price table here, because every team starts from a different place. Here's how we find out where yours starts.

Take the maturity quiz

3 minutes

Eight questions about how your developers actually work with AI today. You get your team's level and how it compares to your peers.

Talk it through with us

30 minutes

You tell us how your team works, and we tell you what we'd do: how many sessions, which roles, in what order. Price comes once the structure is clear, not before.

We work with your team

Days to weeks

Training, coaching, and hands-on setup in your own repo. Real stories from your backlog go through the new setup before we leave, and your leadership gets a final report.

Keep it sharp

Optional

Models and tools change every few months. If you want, we come back on a rhythm you pick, weekly, monthly or quarterly, and keep tuning what your team built.

Book a call

The first call is about your team, not about us.

As heard on

The thinking behind the method.

Founder Juri Kuehn on why AI adoption stalls at autocomplete, and what it takes to get an engineering organization to agentic delivery.

Click to load from YouTube

AI Agents Podcast

EP85 - Building AI Enterprises with Codeligence

with Demetri Panici

Click to load from YouTube

Fraunhofer IEM

Prof. Dumitrescu Tech Talk #43 - KI im Software Engineering

with Prof. Dr.-Ing. Roman Dumitrescu

Why teams pick us.

We ship with agents daily

Everything we teach comes from our own production work with AI agents, built on 30 years of shipping software. None of it comes from a slide deck.

Measured, in writing

We baseline your team first and write the measurement protocol into the contract. At the end you get before-and-after numbers from your own repos, not from a vendor benchmark.

You own everything

The factory lives in your repos, and your team runs it after we leave. We'd rather earn the next engagement than lock you into this one.

Vendor-neutral on tools

Claude Code, Codex, Copilot. We set up whatever fits your stack and measure what matters. We don't sell licenses and we don't sell tool training.

Curious where your team stands today?

Take the free maturity quiz

Why do 95% of AI pilots fail?

Research reports with cited sources on AI adoption, developer productivity, and what separates measurable gains from adoption theater.

Read the Research

Find out what level your team is on.

Eight questions, three minutes. You get a scored level, a peer benchmark, and the one move that takes your team up a level. And if you'd rather just talk it through, book a call and bring your questions.

Take the free quiz Book a call