AI-Powered Software Development
Our AI software development agents act as senior engineers on your team — reviewing pull requests, catching bugs before they reach production, generating unit tests, and implementing features from your backlog. They integrate directly into GitHub, GitLab, and Jira so they work inside the tools your team already uses.
What you get
Managed implementation, workflow setup, and ongoing optimization inside your existing stack.
Best fit
Teams that want faster execution without adding full-time headcount or rebuilding internal processes from scratch.
Production-grade delivery
We configure the agent around your actual tools, approvals, and workflows so outputs are usable from day one.
Built around your process
The service wraps the technology with onboarding, guardrails, and operational handoff instead of leaving your team to figure it out.
Human oversight by design
Review gates, escalation rules, and security boundaries are defined up front before the agent is trusted with live work.
What Hiretecky Does
A service package, not just a tool login
We turn the agent into an operational capability your team can actually use.
Automated Code Review
Every pull request is reviewed for logic errors, security vulnerabilities, code style violations, and performance issues — with inline comments, just like a human reviewer.
Test Generation
AI agents generate unit, integration, and edge-case tests for new and existing code. Coverage gaps are identified and filled automatically.
Bug Detection & Fixes
Static analysis combined with AI reasoning catches bugs that linters miss. For common bug patterns, the agent proposes — or directly applies — fixes.
Feature Implementation
Assign a Jira or Linear ticket to the agent. It reads the spec, writes the code, and opens a PR for your team to review. Works best for well-defined, scoped features.
Documentation Generation
From inline docstrings to full API documentation and README updates — agents keep your docs in sync with your codebase automatically.
Security Scanning
Continuous vulnerability scanning across your codebase, with prioritized remediation suggestions mapped to CVE severity levels.
Deliverables
Clear outputs your team can hold us to
Each engagement ships with documented outcomes, integrations, and reporting so you know exactly what is being deployed.
Works with
Automated PR review on every commit
Test suite with target coverage threshold
Security vulnerability report & remediation plan
Documentation for all new and modified modules
Weekly development velocity report
Integration with GitHub / GitLab / Jira / Linear
Delivery Process
How the engagement rolls out
We start with a narrow pilot, measure output quality, and only expand once the workflow is stable.
Repo Access & Audit
We connect to your repositories and run an initial audit — codebase size, test coverage gaps, common bug patterns, and security posture.
Workflow Configuration
We configure the agent to match your branching strategy, code style guide, review preferences, and escalation rules.
Pilot on One Repo
We run a 2-week pilot on a single repository. You review every agent output before it merges. We tune based on your feedback.
Full Deployment
Expand to your full codebase. Agent runs on every PR, every commit, continuously — with weekly performance reports.
FAQ
Questions teams usually ask before rollout
Can the agent work with any programming language?
DevPilot AI supports all major languages including TypeScript, JavaScript, Python, Go, Java, Ruby, and Rust. Language-specific review depth varies — TypeScript and Python have the strongest coverage.
Will it break our existing CI/CD pipeline?
No. The agent integrates as an additional check in your pipeline, not a replacement. It adds review comments and optional automated fixes — your existing tests, linters, and deployment gates are untouched.
Who has access to our codebase?
Only the agent itself, operating under read/write permissions you define. Your code is never used to train external models. We sign a custom NDA and DPA before any repo access is granted.
What if the agent writes bad code?
All agent-generated code comes as a pull request — nothing merges automatically without human approval. You review it exactly as you would any other PR.