Agent engineering
Python
QwertyBit builds production Python agent pipelines, evaluation harnesses, fine-tuning workflows, and data engineering — with strict typing, tested CI, and observability from the first commit.
QwertyBit is a Python AI development agency. We build production agent pipelines, evaluation harnesses, ETL and data engineering, and fine-tuning workflows in Python — all shipped to your GitHub with strict typing, tested CI, and observability from commit one.
Why Python is our default for agent work
Python wins on three fronts where agents live:
- The AI ecosystem — every library you would reach for exists and is actively maintained.
- Data engineering fluency — Pandas, DuckDB, Polars, SQLAlchemy keep the data side honest.
- Readability — agent pipelines are easier to reason about when the code is legible.
Where we use Python at QwertyBit
- Agent orchestration. LangChain, CrewAI, custom harnesses — all Python.
- ETL and data readiness. Phase 1 and Phase 4 work (business analysis and feasibility) usually includes a pile of Python.
- Evaluation harnesses. The discipline that separates production agents from demos.
- Fine-tuning pipelines when we are running on-prem with LLM Studio.
Where we pair Python with Node.js
Our production systems often have Python on the agent/data side and Node.js on the product/API side. The boundary is a queue or a typed HTTP API. Both languages do what they are best at without stepping on each other.
The engineering standards we apply
Every Python agent repo we ship has:
- Type hints and
mypyon CI. rufffor linting,pytestfor tests,uvfor dependency management.- Isolated evaluation runs that do not require a developer's laptop.
- Observability instrumentation from the first commit.
Further reading
- How to choose the right software architecture for your SaaS MVP — how language choice interacts with architecture.
- Monitoring analytics and KPIs: a beginner's guide — where Python shines in observability.
- Python's own documentation and the Astral ecosystem (uv, ruff).
Work with us on Python
Python-based agent builds and custom data engineering sit across our AI agent development and custom software development services. If you are choosing a stack for your AI product, book a scoping call and we'll sketch the trade-offs with you.
Further reading
Frontier LLMs
Anthropic
QwertyBit builds production AI agents on Anthropic Claude for high-reasoning, long-context, and compliance-aware workflows where steerability matters.
Multi-agent orchestration
CrewAI
QwertyBit builds multi-agent systems with CrewAI for workflows that need specialist agents planning, executing, and reviewing in sequence — not a single oversized prompt.
Version control & CI
GitHub
QwertyBit ships every line of code to your GitHub from commit one — transparent delivery, PR reviews, CI, and no vendor lock-in. Custom software engineering that your team inherits cleanly.
Ready to see where agents can take cost out of your business?
Tell us about the process you want to optimise. Vlad personally reviews every brief and replies within one business day.