Services · Remote delivery worldwide
I build bounded AI workflows with clear tool permissions, approval steps and recovery paths. Start with one valuable operation so external actions remain understandable and controlled.
Get a free estimateDefine the expected behavior of tool contracts and permissions against the chosen ai agent development workflow. Include the inputs, visible result and recovery condition, with special attention to unapproved external actions. The handoff should explain the boundary another developer can safely extend.
Define the expected behavior of durable operation state against the chosen ai agent development workflow. Include the inputs, visible result and recovery condition, with special attention to repeated side effects. The handoff should explain the boundary another developer can safely extend.
Define the expected behavior of human approval screens against the chosen ai agent development workflow. Include the inputs, visible result and recovery condition, with special attention to stale permission context. The handoff should explain the boundary another developer can safely extend.
Define the expected behavior of bounded execution loops against the chosen ai agent development workflow. Include the inputs, visible result and recovery condition, with special attention to lost workflow checkpoints. The handoff should explain the boundary another developer can safely extend.
Define the expected behavior of recovery and escalation against the chosen ai agent development workflow. Include the inputs, visible result and recovery condition, with special attention to infinite retry loops. The handoff should explain the boundary another developer can safely extend.
Define the expected behavior of evaluation traces against the chosen ai agent development workflow. Include the inputs, visible result and recovery condition, with special attention to unapproved external actions. The handoff should explain the boundary another developer can safely extend.
AI agents go beyond chatbots — they plan, take actions, and close loops without you having to click through every step. I design and build AI agents that integrate with your existing tools (email, CRMs, databases, APIs, Slack) and automate repetitive, multi-step workflows.
The key difference from simple automation: agents can handle ambiguity and variation — they read context, make decisions, and adapt — unlike rigid if/then scripts.
Planning ranges below are illustrative; a delivery schedule is agreed after reviewing your actual scope.
1–3 working days (planning assumption)
For ai agent development, this step concentrates on tool contracts and permissions and the risk of unapproved external actions. Identify the users, existing dependencies and the first useful workflow. Write the acceptance conditions before estimating a build. The schedule depends on access, review turnaround and the complexity of the systems involved; these ranges are planning examples, not a delivery promise.
2–5 working days (planning assumption)
For ai agent development, this step concentrates on durable operation state and the risk of repeated side effects. Map the interface and investigate the riskiest dependency with a narrow prototype. Capture unanswered questions instead of treating a mockup as a finished system. The schedule depends on access, review turnaround and the complexity of the systems involved; these ranges are planning examples, not a delivery promise.
Scope-dependent; estimate after discovery
For ai agent development, this step concentrates on human approval screens and the risk of stale permission context. Build a small vertical slice that connects the interface, application logic and persistence. Review that slice before expanding to additional workflows. The schedule depends on access, review turnaround and the complexity of the systems involved; these ranges are planning examples, not a delivery promise.
2–5 working days per agreed milestone
For ai agent development, this step concentrates on bounded execution loops and the risk of lost workflow checkpoints. Check the accepted behavior with realistic fixtures, denied actions and interrupted requests. Review accessibility, logs and recovery paths as part of the same milestone. The schedule depends on access, review turnaround and the complexity of the systems involved; these ranges are planning examples, not a delivery promise.
1–3 working days (planning assumption)
For ai agent development, this step concentrates on recovery and escalation and the risk of infinite retry loops. Prepare configuration notes, deployment steps and ownership. Demonstrate one normal operation and one failure recovery so maintenance does not depend on memory. The schedule depends on access, review turnaround and the complexity of the systems involved; these ranges are planning examples, not a delivery promise.
Node.jsAutomation: schedule meeting on Google Calendar; bot auto-joins via Vexa AI; transcribes and takes notes; sends summary to stakeholders. Streamlined meeting documentation.
TODO: Add an owner-verified measurable outcome and measurement period.
AI tool assisting business development workflows — lead research summarization and first-draft proposal generation.
TODO: Add an owner-verified measurable outcome and measurement period.
AI chat assistant backed by a knowledge graph for structured domain Q&A — grounding responses in a curated entity/relationship graph instead of free-form retrieval alone.
TODO: Add an owner-verified measurable outcome and measurement period.
TODO: Add a genuine client testimonial relevant to ai agent development, with permission and a source link. No unverified quote is shown here.
Third-party subscriptions, hosting and specialist reviews are scoped separately. An estimate states assumptions and exclusions before work starts.
Starting from: TODO — owner to confirm range
A defined workflow with acceptance criteria and milestone payments. Changes outside the agreed scope receive a separate estimate.
Starting from: TODO — owner to confirm range
Useful for investigation, targeted improvements and evolving requirements. Agree on a time budget and review progress before extending it.
Starting from: TODO — owner to confirm range
Reserved capacity for maintenance and iterative delivery. Agree on included work, response expectations and a monthly review.
Start with the users and the workflow that matters most. For this service, share examples related to tool contracts and permissions, current systems and any constraints on data access. Include a target date and budget range. This makes it possible to distinguish necessary work from optional additions before proposing a milestone.
I separate the initial workflow from secondary features, then review durable operation state and the dependencies it introduces. An estimate should list assumptions, exclusions and acceptance checks. Unknowns such as repeated side effects may need a short investigation before a fixed commitment is sensible.
An existing Python implementation can be the starting point. I would review the relevant code, configuration and current behavior first, then propose a narrow change. Access to a staging environment and reproducible examples helps assess stale permission context without relying on live customer records.
The acceptance conditions should cover successful completion and a deliberate failure. For human approval screens, we agree on representative fixtures and the expected user-visible state. Tests should verify the actual boundary rather than just the shape of a response. Any specialist compliance or security review is scoped separately.
The application needs a defined response to lost workflow checkpoints. Depending on the workflow, that may be a retryable state, preserved input, an operator queue or a human handoff. We should decide which actions are safe to repeat and what evidence support staff need before accepting the design.
Ownership of the ai agent development deployment, credentials and operational checks is agreed before release. The handoff documents recovery and escalation and the remaining support needs. Ongoing maintenance can be discussed as a separate engagement; it should not be assumed to include unlimited features, platform changes or external-provider costs.
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