Picture your release process as a busy airport at night. Planes (features) are lining up, weather (risks) is shifting, and timing is everything. An AI IT release coach agent is the calm, tireless air-traffic controller plus a seasoned coach whispering in your ear at the same time.
...gives you confidence and eventually brings you success...
What AI Model is used by mikloskadar.com?
Our AI Release Coach service is model agnostic and at this stage of the AI industry we intend to keep it that way. As a general rule as of right now for our basic service we usually use GPT from OpenAI, but for client specific reasons we can configure our release management knowledge behind all major models (GPT Pro, Gemini, Grok, Claude, Sonar or DeepBlue, etc.)
Is a specialized AI relase coach better than free AI prompts?
Try it out! Generative AI chat bots (ChatGPT, Gemini, Claude etc.) are generally good at many things but they are not trained on a specific subject, which means:
General AI bots cannot really tell the difference between outdated and fresh methodologies
Their knowlegde base is not specialized and not updated in a focused way.
They take all release approaches at more or less the same weight
mikloskadar.com trains its AI Release Coach with all new information of release management trends and best practices on a regular basis
mikloskadar.com's AI Release Coach has the knowledge of a lifetime spent in release management
What is happening with your company data that you give to the AI?
mikloskadar.com is based in the EU hence complying to all related EU regulations:
GDPR (Regulation (EU) 2016/679)
EU AI Act (Regulation (EU) 2024/1689)
DSA (Regulation (EU) 2022/2065)
The AI industry is very turbulent. How stable is this service and the company behind?
At the moment all AI projects and related services are in their early stages. Most projects that are using AI can be called pilot projects together with our own AI project, but in our case it is a pilot of a new form of delivering the same consulting service to our clients. Digital technologies come and go. Major IT platforms emerge, merge and disappear. But the founder of mikloskadar.com, Mr. Miklos Kadar, has been in release management for well over 25 years and the mikloskadar.com brand is almost 20 years old. mikloskadar.com's service is release management knowledge transfer. So the service of knowledge transfer is stable while the form of delivering the release management knowledge transfer service keeps changing. The form of release management knowledge transfer can either be personal coaching, remote consulting, on-site and online training courses, books, posts, emails, phonecalls, chat messages, and now AI enhanced release coaching. The forms of knowledge transfer can change, the professional senior content can only refine. Hence I would say our service is stable and has been stable for 25 years. This new form: AI Release Coaching just makes our service more accessable to many.
It doesn’t just track tasks, it advises:
Suggests release timing based on risk, dependencies, and team readiness
Recommends rollout strategies (big bang vs phased vs feature flags)
Flags when “this feels rushed” even if no one said it out loud
Think: a digital version of a battle-hardened release manager who has seen every failure mode.
The agent constantly scans signals:
Code changes (PR size, frequency)
Test results and coverage gaps
Dependency conflicts
Environment drift
Then it raises things like:
“This release has 30% more changes than usual”
“Critical component modified without regression coverage”
It turns hidden landmines into visible warning signs.
Instead of you chasing Jira tickets and pipelines:
Tracks readiness across teams (dev, QA, ops)
Monitors CI/CD pipelines (GitHub, Jenkins, etc.)
Ensures all gates are met before release
It’s like having a real-time release dashboard that thinks.
It learns patterns over time:
Which changes caused past incidents
Which teams tend to under-test
Where bottlenecks happen
Then it suggests:
Extra testing where risk is high
Rollback plans before you need them
Better branching or deployment strategies
No more scattered Slack threads:
Summarizes release readiness in plain language
Notifies stakeholders of risks and status
Generates release notes automatically
Example:
“Release readiness: 82%. Blocking issue in payment service. Recommend delaying 24h.”
Over time it becomes your coach:
Adapts to your release cadence (weekly, monthly, CI/CD)
Understands your architecture and dependencies
Aligns with your governance (important for enterprises… your world)
It plugs into things like:
GitHub / GitLab (code + PRs)
Jenkins / CI pipelines
Jira / Azure DevOps (tickets)
Monitoring tools (post-release health)
So it’s not another tool… it’s the brain across tools.
If you are a release stakeholder, this is the interesting part:
An AI release coach doesn’t replace a release manager but it amplifies one into a control tower.
You can move from:
chasing updates
manually assessing risk
coordinating people
to:
making decisions based on intelligent insights
focusing on governance and strategy
scaling across multiple releases without burnout