Agentic Software Engineering with AI Coding Agents Corporate Training
Put AI coding agents to work on real features, with guardrails your team trusts.
This instructor-led program gives development teams practical methods for engineering software with AI coding agents, from agent workflows and context engineering to multi-agent orchestration, tool integration, and the evaluation and safety guardrails that keep agent-built software trustworthy. Every technique is validated through hands-on labs.
Instructor-led group trainingVirtual / on-site / off-site10 languagesDelivered inEnglish, Spanish, Mandarin, German, Arabic, Portuguese, Hindi, French, Japanese, Italian100+ countriesWe have delivered inUnited States, United Kingdom, India, Canada, Germany, France, Netherlands, UAE, Saudi Arabia, Singapore, Australia, Japan, Brazil, South Africa and 90+ more countries
How we build an agent-powered team
The Edstellar AGENTIC SOFTWARE ENGINEERING WITH AI CODING AGENTS Capability Model
Diagnose agent opportunities
We review your coding workflows and delivery bottlenecks to find where AI coding agents pay off fastest.
Standardize agent workflows
Your team learns one shared set of agent patterns, context conventions, and verification gates for agentic coding.
Practice in guided labs
Developers ship real features with AI coding agents in hands-on labs, coached on orchestration and guardrails.
Measure delivery outcomes
You track cycle time, agent success rates, and defect rates to prove agents are accelerating delivery safely.
Scale what works
Winning agent patterns and evaluation suites become team playbooks your whole organization can adopt.
Need more than one program?Get a group quote
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Program Overview: What is Agentic Software Engineering with AI Coding Agents?
Agentic Software Engineering with AI Coding Agents is Edstellar's instructor-led technical program for engineering teams building software with AI agents. Participants learn agent workflows, context engineering, multi-agent orchestration, tool integration, and evaluation and safety guardrails. The focus stays on production practice: agents that plan, write, test, and iterate on code under human supervision.
Training is hands-on from the first module. Participants map the agentic coding landscape, then design plan-execute-verify workflows with human-in-the-loop checkpoints in guided labs. Instructors coach your team through context engineering on real repositories, orchestrating subagents, and wiring MCP servers and CI hooks, reviewing every exercise with direct feedback. The program closes with a capstone where the team ships an agent-built service with full evidence.
Teams adopting coding agents often get fast output they cannot trust: untested changes, lost context, and no review trail. This program teaches your engineers to run agents like a discipline, with verification gates, review queues, and safety guardrails on every run. Every technique is practiced in labs, so the workflows transfer directly to your codebases.
Engineers build and ship a service using AI coding agents end to end, tests, reviews, evidence included. By the end, your team knows exactly where coding agents accelerate delivery and where human judgment stays non-negotiable.
Over 28 instructor-led hours, participants move from agent fundamentals to a complete capstone service. They design plan-execute-verify loops, engineer repo context agents can trust, orchestrate subagents across complex tasks, integrate MCP tools and CI hooks, and build evaluations that catch agent failures. Every lab mirrors real engineering work, so teams leave with workflows they can use on their own codebases immediately.
What's Included in this Workshop for Your Enterprise Teams
- 1
Foundations
Understand how AI coding agents plan, act, and verify across development tasks.
- 2
Workflows
Design plan-execute-verify loops with human checkpoints for agent tasks.
- 3
Context
Engineer repository context agents can trust: docs, memory, and tools.
- 4
Orchestration
Coordinate subagents across complex, multi-step engineering work.
- 5
Guardrails
Evaluate agents and enforce safety before agent code reaches production.
- 6
Capstone
Ship an agent-built service with full tests, reviews, and evidence.
- Instructor-led delivery across virtual, onsite, and hybrid formats
- 28 hours of guided instruction with hands-on labs in every module
- Course materials, agent pattern libraries, and evaluation templates included
- Trainers with real agentic coding experience in production teams
- Cohort scheduling aligned to your team's availability and time zones
- Post-program support resources for applying workflows to live projects
Build your team's skills. Anywhere in the world.
Real-world use cases
from day one
Instructor-led training
for your teams
Delivered globally
in 100+ countries
Enterprise Training Solutions Customized for Your Company
One partner for instructor-led corporate training, delivered the way your teams work.
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Agentic Software Engineering with AI Coding Agents Course Topics and Program Outline
Seven modules take your team from agent fundamentals to a complete capstone: workflows, context engineering, orchestration, tool integration, and evaluation guardrails.
Built by Edstellar with agentic engineering specialists
Built by engineers who ship production software with AI coding agents every day, shaped around your stack and use cases.
We review your coding workflows, review queues, and delivery speed to find where AI coding agents pay off fastest.
Your team learns how coding agents work, plan-execute-verify workflows, and the setup that fits your repositories.
Developers orchestrate subagents and integrate tools in guided labs, coached on context and verification discipline.
Teams wire MCP tools and CI hooks into agent runs and ship a production-ready capstone service with full evidence.
Outcome: a production-ready service built with AI coding agents, with tests, reviews, and workflow evidence.
Delivered as
Delivered as 28 instructor-led hours with a guided lab in every module and a capstone service your team builds, tests, and presents.
Run your first agentic coding task end to end and map where the agent needed human help.
learna)Agents versus assistants: plan-execute-verify loops
b)Tool use: how agents read, write, and run code
c)The agent landscape: CLIs, IDE agents, and platforms
d)Where agents excel and where humans must stay in the loop
Design a plan-execute-verify workflow for a feature, then run it with an AI coding agent.
learna)Task decomposition: breaking work into agent-sized steps
b)Planning documents and checkpoints before execution
c)Human-in-the-loop: when to approve, steer, or stop
d)Verification gates: tests and reviews after agent runs
Onboard an agent onto your repo with context docs and safe permissions, then ship a scoped change.
practicea)Onboarding agents onto unfamiliar repositories
b)Context engineering: docs, specs, and conventions
c)Permissions and sandboxing for safe agent runs
d)Recovering context when agents get lost
Orchestrate parallel subagents to explore, build, and review a feature, then integrate their output.
practicea)Orchestrator and worker patterns for coding tasks
b)Parallel subagents: exploration, build, and review
c)Handoffs and shared context between agents
d)Debugging orchestration failures
Connect an MCP server and a CI hook so an agent run opens a tested, review-ready pull request.
applya)MCP servers: connecting agents to docs and systems
b)Agent hooks in CI: automated checks around agent runs
c)PR automation: agents that open review-ready changes
d)Observability: logging and tracing agent activity
Build an evaluation checklist and review queue for agent changes, then harden the risky parts.
practicea)Evaluating agents: task success and failure modes
b)Review queues for agent-generated changes
c)Security and cost guardrails for agent runs
d)Rollback and containment when agents misbehave
Ship a reviewed, tested service built with AI coding agents and present the workflow evidence to your cohort.
applya)Capstone brief: service scope and acceptance criteria
b)Build with agents: plans, subagents, and tooling
c)Evaluations, reviews, and guardrails on every change
d)Demo and delivery retrospective
Customize this program tailored to your team?
Tell us your training needs: what your team already works with, the level they’re at, and the topics you want them to focus on. We’ll adjust the modules, duration and hands-on labs, and send you a customized outline for your group.
Key Skills and Outcomes Your Team Will Gain
Every participant leaves with agentic coding workflows they can use on their own codebases the week after the program.
Map agent opportunities
Find the coding work where AI agents deliver the biggest payoff.
Design plan-execute-verify loops
Scope agent tasks with plans, checkpoints, and human oversight.
Engineer agent-ready context
Give agents docs, memory, and permissions they can trust.
Orchestrate subagents
Coordinate parallel agents across complex, multi-step work.
Integrate tools and CI hooks
Wire MCP servers and pipelines into agent workflows.
Evaluate and guard agents
Catch agent failures with evaluations, reviews, and safety controls.
Ship agent-built services
Deliver production services with agents, backed by tests and review evidence.
Teams that Benefit from this Agentic Software Engineering with AI Coding Agents Group Training
This program is built for software developers, tech leads, and engineering managers adopting AI coding agents. Content adapts to each cohort's stack and maturity, so every group practices the engineering workflows it actually owns.
Ship features with AI coding agents
Developers learn to design agent workflows and verify agent-built features across the products they own.
Workflow friction
- Complex multi-step coding tasks
- Agents losing repo context
- Agent output nobody verifies
How the program helps
- Faster feature delivery with agents
- Workflows tuned to your codebase
- Review habits that catch agent mistakes
Practice use cases
- Feature development
- Agent patterns
- Agent code review
- Service scaffolding
Make agentic coding safe at scale
Platform teams learn sandboxing, permissions, MCP tooling, and guardrails for agent runs.
Workflow friction
- Uncontrolled agent permissions
- Runaway agent costs
- Agents touching sensitive systems
How the program helps
- Safe agent sandboxes
- MCP tooling for internal systems
- Guardrails across agent runs
Practice use cases
- Agent sandboxes
- MCP integration
- Cost guardrails
Verify agent-built software before release
QA engineers learn to evaluate agents and validate the tests and code agents produce.
Workflow friction
- Agent-generated test gaps
- Nondeterministic agent behavior
- Flaky agent-driven pipelines
How the program helps
- Agent evaluation suites
- Faster regression feedback
- Coverage of agent blind spots
Practice use cases
- Agent evaluations
- Test review
- CI automation
Prove agents move delivery metrics
Leads learn to measure agent adoption, track delivery impact, and scale what works.
Workflow friction
- Unclear agent ROI
- Uneven team adoption
- Quality slipping with speed
How the program helps
- Delivery metrics that prove impact
- Adoption playbooks for teams
- Safer enterprise rollout
Practice use cases
- Adoption metrics
- Team playbooks
- Rollout planning
Every cohort blends methods with the engineering workflows your teams own, so practice time maps directly to your products.
Prerequisites: This program suits software developers, tech leads, QA engineers, and engineering managers. No prior AI experience is needed; everyday coding fluency is enough. Teams with active codebases get the fastest payoff by practicing on their own repos. The program adapts examples, labs, and the capstone brief to each cohort's stack and workflow.
Developer to agentic delivery owner
Teams start with agent fundamentals and workflow design, then engineer context and orchestrate subagents through guided labs, finishing with tool integration, evaluations, and a capstone service shipped with full evidence.
One program that grows with engineering careers, from agent basics to confident agentic delivery ownership.
Mixed cohort, or several teams at once?
We can tailor the training to different teams, roles, and experience levels within the same program.
Certificate of Training Completion.
On successful completion, employees receive an Edstellar course completion certificate, recognizing their commitment to ongoing learning and professional development. It validates the skills they have built and motivates them to keep growing and contribute to organizational success.
Earned, not attended. Awarded on completion of all hands-on labs and the capstone project.
Training Delivery Modes: Virtual, Onsite and Hybrid
Choose the format that fits your team: live virtual for distributed developers, onsite at your office for intensive cohorts, or hybrid combining both.
Hybrid Training
A blended schedule with virtual sessions and onsite lab days. Your team gets remote flexibility plus in-person collaboration for agent labs and the capstone service.
- Flexible mix of virtual and onsite sessions
- Onsite lab days for agent orchestration
- Cohorts across locations in one program
- Schedule shaped around sprint cadence
Onsite Training
The full 28 hours delivered at your location. Whiteboard design sessions and face-to-face capstone demos make this the most immersive way to learn agentic coding.
- Immersive full-day or multi-day cohorts
- Hands-on labs with your codebase
- Capstone demos to your stakeholders
- No travel cost for your team
Live Virtual Training
Live virtual sessions with breakout labs using AI coding agents on your repos. Teams practice workflows, orchestration, and guardrails in real time with instructor coaching.
- Live instructor sessions with breakout labs
- Labs using your agent toolset
- Session recordings for review
- Ideal for distributed engineering teams
Need a training format that works for your team?
Full days, half days across weeks, or split by module. Tell us the delivery window and we schedule the cohort around it.
Frequently Asked Questions
Share your team size and preferred format through the quote form. We respond with pricing and scheduling options within one business day.
Yes, a short call with an advisor maps your stack, team size, and goals to the right program shape.
Yes, instructor-led live virtual delivery with breakout labs runs in your time zones.
Yes, onsite cohorts are available for intensive multi-day delivery with your own tooling.
28 instructor-led hours across seven modules, ending with a capstone service build.
Question not answered here?
Put it in the request. A training specialist answers it directly, within one business day.
Where this Training Fits in Your Team's learning path.
Agentic engineering goes a step beyond AI code completion. Your developers start with an AI assistant, then hand multi-step tasks to coding agents, evaluate and guard what those agents do, and secure the delivery pipeline so agent-written code ships safely.
Why Choose Edstellar as Your Corporate Training Provider for Agentic Software Engineering with AI Coding Agents Course
Edstellar delivers Agentic Software Engineering with AI Coding Agents as hands-on, instructor-led training for development teams. Labs mirror real agentic engineering work, the capstone produces a service your organization can ship.
EXPERT TRAINERS
YEARS DELIVERING
ORGANIZATIONS TRAINED
CERTIFIED
Tailored
Labs and the capstone brief are built around your codebases and agent tooling, so practice maps to the engineering work your teams own.
Proven Methodology
A structured sequence from agent fundamentals to multi-agent orchestration, refined with working development teams.
Practice-Based Learning
Every module runs a guided lab with AI coding agents on your repos, so skills form through real engineering work.
Expert Trainers
Trainers ship with AI coding agents daily and coach your teams on workflows, evaluation, and safety.
Global Scale
Cohorts run across your time zones with consistent materials, labs, and instructor quality.
Measurable Outcomes
You track delivery speed, agent success rates, and adoption from the first cohort onward.
Develop Agentic Coding Workflows With Tests, Review, and Evidence
Edstellar helps engineering teams use coding agents within an explicit plan, execution, and verification process. Participants prepare repository context, coordinate subagents, connect tools and CI, and inspect generated changes. A reviewed service build brings these practices together, with evidence showing where automation worked and where human judgment remained necessary.
- Step 01
Consult
We review coding workflows and repository practices to identify suitable agent tasks, missing context, verification gaps, and situations that require explicit human review.
- Step 02
Plan
We progress from a first coding-agent task through plan-execute-verify loops, repository context, subagents, and integrations before reviewing a complete agent-built service.
- Step 03
Align
We align instruction with everyday coding fluency and the cohort’s development tools, making repository permissions, test availability, and review responsibilities explicit before agent exercises.
- Step 04
Customize
We tailor feature briefs, context documents, and integration tasks to familiar codebases, keeping changes scoped and providing clear boundaries for parallel agent work.
- Step 05
Execute
Participants run coding agents, integrate subagent outputs, and connect CI checks, receiving feedback on context quality, change scope, test evidence, and review decisions.
- Step 06
Evaluate
We assess the service and workflow evidence for tested functionality, coherent integration, permission discipline, and a clear account of how agent-generated changes were verified.
Also from Edstellar
Talent assessments
Psychometric, behavioral, leadership and 360-degree assessment.
→Training needs analysis
Needs analysis, gap identification, and a training roadmap.
→L&D consulting
Learning strategy, content, technology and ROI measurement.
→OD consulting
Org design, succession planning and cultural change.
→Managed training services
Training outsourcing, vendor management, logistics and administration.
→Coaching solutions
Executive and manager coaching that keeps skills in use.
Start an RFP shaped to your needs.
Answer three quick questions about team size, scope, and how often you need the program run, then send the request from the last step. Everything you choose travels with it, so you only fill this in once.
How many team members need training?
Agentic Software Engineering with AI Coding Agents Training Packages & Pricing
Where L&D holds an annual budget, license packages price the whole year at once instead of raising a purchase order per workshop. Hours and licenses are pooled across teams, programs and locations, so unused capacity is not stranded in one department.
Starter
120
trainee licenses64 hours of group training
Tailored for SMBs
Growth
320
trainee licenses160 hours of group training
Ideal for growing SMBs
Enterprise
800
trainee licenses400 hours of group training
Designed for large corporations
Custom
Unlimited
trainee licensesDuration set by the rollout
Multi-region and multi-year
Training Packages & Pricing
Choose the training format that works for your team. Pricing is customized based on your requirements, cohort size, and delivery needs.
Request Agentic Software Engineering with AI Coding Agents Training for Your Team
Tell us about your development teams and agent tooling. We will tailor the labs and capstone brief to your stack and workflows.