Shelpuk & Company
    AI Engineering Enablement

    Unlock AI-Powered Development for Your Teams

    We help engineering teams select, configure, and adopt the right AI coding tools. Tailored to each team's stack, workflow, and goals.

    4–6 week engagement

    Why AI tool adoption fails

    Most teams buy AI tools but never see the promised productivity gains. Here's why.

    Tool overload, unclear ROI

    Dozens of AI coding tools, but which ones actually work for your stack? Most teams waste months experimenting without results.

    Generic configurations fail

    Out-of-the-box AI tools don't understand your codebase, architecture, or workflows. They need tailoring to deliver value.

    Adoption stalls without guidance

    Engineers try AI tools once, get mediocre results, and abandon them. Real adoption requires hands-on enablement.

    Our approach to enablement

    We don't do generic training decks. We go deep with each team.

    Team-Specific Approach

    No one-size-fits-all. We tailor tool selection and configuration to each team's unique stack, domain, and workflow.

    Deep Configuration Expertise

    We don't just recommend tools — we configure MCP servers, write custom skills, and tune prompts for your codebase.

    Hands-On Enablement

    Theory doesn't drive adoption. Pair programming and real-world practice with your actual codebase does.

    Measurable Outcomes

    We track adoption metrics and productivity gains. You'll know exactly what ROI the engagement delivered.

    Open Source

    Built by Us, Validated by the Community

    We don't just configure third-party tools — we build our own. These open-source projects power our enablement engagements and are trusted by thousands of developers worldwide.

    350+ GitHub Stars
    3,000+ developers
    3 products open-sourced

    Kindly Web Search

    Noise-resistant web search with full content extraction

    Learn More

    Lad Code Review

    Project-aware AI code review for coding agents

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    TDD for AI Agents

    Reusable TDD workflow skill for Codex & Claude Code

    Learn More

    How we enable your teams

    A structured 4–6 week engagement from discovery to sustained adoption.

    01
    Week 1

    Leadership Alignment

    We interview your engineering leadership to understand strategic goals, constraints, and success metrics.

    02
    Week 1

    Workshop

    A 2-hour workshop for engineers on AI coding tools, their limitations, and practical ways to overcome them. This brings every team to the same page before individual interviews.

    03
    Week 1-2

    Team Interview

    Deep-dive with each team — a C++ embedded team has different needs than a React mobile team. We map tools, processes, and pain points.

    04
    Week 2-3

    Tool Selection & Config

    We select the right AI tools for each team and configure them: MCP servers, skills, prompts, and workflow integrations tailored to your stack.

    05
    Week 3-5

    Deployment & Enablement

    Hands-on deployment with each team. Pair programming sessions ensure engineers are productive with the new tools from day one.

    06
    Week 5-6+

    Coaching & Iteration

    Ongoing support to refine configurations, address blockers, and track adoption metrics across teams.

    What you'll receive

    Everything your teams need to become AI-augmented developers.

    Tool Recommendations

    Team-specific AI tool stack recommendations based on your codebase, workflows, and constraints.

    Custom Configurations

    Tailored MCP servers, skills, prompts, and integrations configured for each team's needs.

    Training Workshops

    Hands-on sessions for each team covering tool usage, best practices, and workflow integration.

    Pair Programming Sessions

    Real-world coding sessions with your engineers to ensure immediate productivity gains.

    Workflow Documentation

    Documented processes and playbooks for sustained AI-augmented development practices.

    Ongoing Coaching

    Post-deployment support to refine tools, troubleshoot issues, and maximize adoption.

    Case Study

    Enterprise SaaS Company

    Enterprise Software

    Challenge

    12 engineering teams across 4 tech stacks (Java, TypeScript, Python, Go). Previous AI tool rollouts failed due to generic configurations and lack of training.

    Outcome

    5 teams enabled in 6 weeks. 40% reduction in code review cycles. 3 teams now using custom MCP servers for internal APIs.

    "They understood that our backend team and mobile team need completely different setups. That insight made all the difference."

    — VP of Engineering, Enterprise SaaS Company

    Frequently Asked Questions

    Answers to common questions about this topic.

    How can we train engineering teams to work effectively with AI tools?

    This service trains engineering teams to use AI tools with repeatable workflows, governance guardrails, and measurable productivity targets. Shelpuk AI Technology Consulting helps engineering leaders convert AI adoption goals into repeatable operating practices.

    What does the enablement approach include in day-to-day practice?

    In this context: Train your developers to use AI coding tools effectively and measure the productivity gains. Programs combine workflow redesign, tooling standards, coaching, and governance updates to institutionalize AI-assisted software delivery. Shelpuk AI Technology Consulting runs hands-on enablement programs tailored to delivery context, constraints, and maturity.

    How are pricing and scope defined for enablement programs?

    Pricing depends on team count, program duration, coaching intensity, and measurement depth, with phased options from 4 to 8 weeks and multi-quarter tracks. Shelpuk AI Technology Consulting designs scoped enablement engagements with transparent milestones and executive-level reporting.

    How are productivity and quality gains measured over time?

    Progress is measured with baseline-to-target metrics such as cycle time, review throughput, defect trends, and adoption quality indicators. Shelpuk AI Technology Consulting builds measurement frameworks that connect tooling adoption to real delivery outcomes.