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Everyone says they build with AI now.
But is it a habit or a process?
AI agents can turn a day of work into an hour, but that only holds up when someone has defined how they work and who signs off. We built X Tallium agents that carry our engineering standards, security rules, and review gates.
Yesterday
AI as co-pilot
AI in development meant a developer asking a chatbot how to approach something. That’s still the most common version of it, and the one most agencies mean when they tell you they use AI.
AI in development meant a developer asking a chatbot how to approach something. That’s still the most common version of it, and the one most agencies mean when they tell you they use AI.
Now
AI as operator
AI agents write the code inside standards our engineers set per project, and a senior approves every merge. The work that used to sit with a developer for a day can move in an hour.
AI agents write the code inside standards our engineers set per project, and a senior approves every merge. The work that used to sit with a developer for a day can move in an hour.
Two ways we build, with one standard for quality
Both run the same delivery process, the same review gates, and the same senior engineers. What changes is who does the mechanical work.
Who writes the code:
What engineer does:
When we recommend it:Classic Development
Who writes the code:
Our engineers, line by line. AI is available as a consultant if the project allows it
What engineer does:Authors the work, then reviews it.
When we recommend it:In regulated systems where code and data can’t be shared with an LLM, or AI is restricted by policy.
Accelerated Agentic Development
Who writes the code:
Tallium agents operate within the standards set by our engineers, with a senior approving each merge.
What engineer does:Defines the task, sets limits, evaluates results, and takes responsibility using senior judgment.
When we recommend it:In commercial software, speed and coverage are crucial, with no restrictions on the work process.
Ready to ship faster without compromising quality?
Bring us what you’re building and we’ll walk you through our approach and what you’d get at the end.
120+
In-house IT-professionals
250+
Projects delivered
15+
Years on the market
The same SDLC, run by a different
mix of people and Tallium agents
With Accelerated Agentic Development, every project runs through the lifecycle we’ve always used. Discovery and requirements at the start, design and architecture next, then development, QA, release and support. Agents didn’t replace any of that, and no stage was dropped to make room for them.
Discovery
& Concepts
Requirements analysis & workshops- Software requirements specs
- Work breakdown & estimate
- Technical architecture
Human buildsAI builds
Prototypes
& Design
Design concepts- App map / UX flow
- Wireframes & UI/UX designs
- Roadmap & design handoff
Human buildsAI builds
Development
& QA
Project & infrastructure set-up
(CI/CD, database)- Feature development
- Code review, debugging & staging
- Test plan, manual
& E2E automation - Performance testing
Human buildsAI builds
Deployment
& Support
Internal acceptance validation- Client demo & review (UAT)
- Production deployment & release notes
- Support, bug fixing & improvements
Human buildsAI builds
What changes for each person on your team
Business Analyst
Before:- Wrote tickets and specifications by hand
- Found contradictions in requirements once development hit them
- A prototype meant a separate mini-project
Now:- Reviews AI-drafted specs and decides what’s right
- Gets gaps and contradictions flagged before work starts
- Tests an idea with a clickable prototype in a day
Business Analyst
Before:- Wrote tickets and specifications by hand
- Found contradictions in requirements once development hit them
- A prototype meant a separate mini-project
Now:- Reviews AI-drafted specs and decides what’s right
- Gets gaps and contradictions flagged before work starts
- Tests an idea with a clickable prototype in a day
Solution Architect
Before:- Drew diagrams and wrote up decisions by hand
- Weighed alternatives from memory and experience
- Checked architectural compliance by eye during review
Now:- Makes the decision, then reviews the generated diagram and write-up
- Gets alternatives and trade-offs laid out, then chooses
- Every change is checked against the architecture rules automatically
Senior Developer
Before:- Wrote code by hand most of the day
- Read every line in review
- Handled one piece of work at a time
Now:- Defines the work for agents and reviews what comes back
- Reviews logic, design and edge cases after the first pass is done
- Runs two to four workstreams at once
QA Engineer
Before:- Hand-wrote test cases and automation
- Regression testing held up every release
- Wrote up bugs manually
Now:- Designs the test strategy and verifies the critical paths
- Validates the regression tests agents generate
- Gets a drafted bug report with steps, logs and a likely cause
Client / Stakeholder
Before:- Waited weeks to see anything clickable
- Discovered scope gaps in the middle of development
- Chased the team for status updates
Now:- Clicks through a working prototype in the first week
- Sees risks and trade-offs before the budget is committed
- Gets clear progress summaries without asking
What Accelerated Agentic Development brings you
Most changes happen inside our team. On your side, you'll notice four things.
Same budget, more value
Agents handle the routine work, so more of your budget goes into the product itself. What's included is agreed per project and written into the estimate.
Faster delivery
Development tasks complete faster and review cycles get shorter, so you're waiting less between asking for something and seeing it.
Lower cost of change
You see working increments as they land. If you want something different, we can afford to experiment.
You’re not dependent on us
Everything gets documented as the work happens. Any team that picks up the product later has the trail to follow, so you're never locked in to us.
But will AI code quality be any good?
We get the hesitation, so we built guardrails.
Engineer Approval
Agent proposes, a senior engineer reviews and approves. Nothing reaches your product without a person deciding it should.
Agent Standards
Our engineering standards are written into the agent’s instructions per project, so the code is held to our bar.
Reviewed Changes
Agents work in small chunks with acceptance criteria. Automated unit tests and dedicated QA run on top of human review.
Decision Path
Every feature carries a written trail from requirements to test. Want to know why something was built the way it was? Read it at any time.
Your IP, Your Own
Nothing you share is retained or used to train a model. IP ownership and data handling are the same as on any classic project.
Equal Project Guarantees
Nothing you share is retained or used to train a model. IP ownership and data handling are the same as on any classic project.
Questions clients ask most often
Everything you need to know about how we leverage Accelerated Agentic Development to build high-quality software faster.
We quote every project on what it takes to build, so if we go this route, the estimate reflects the work Tallium AI agents take off our engineers. What that usually buys you isn't a smaller invoice so much as more inside it, since the routine work costs less and the time goes into test coverage, documentation, and more product work instead.
Yes. It works whether we're building something new, adding features to what you have, or modernising something older. The agents work from your codebase and the standards we set for the project, so what they write follows the conventions already there.
We work with Claude Code, with agents and standards we've built on top of it for each project. If your organisation has already settled on particular tools or a particular cloud, tell us early and we'll work out what fits.
Then we build the classic way, and nothing you share touches an AI model. Worth raising early, because it's one of the first things we check before recommending an approach.
You do, exactly as on any other project with us. That includes the code, the tests, the architecture decisions and the documentation. Nothing you share with us is retained or used to train a model.
Yes. It's the same team and the same process either way, and some projects genuinely suit it better. If your code can't be shared with an LLM, or your policy rules out AI in the delivery chain, classic is the right answer and we'll say so.
Let’s talk about Accelerated Development
Share the details of your AI idea and we’ll get back to you to set up a call to discuss your project
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