Senora helps engineering organizations build and run software delivery workflows with AI agents—connecting planning, implementation, and production through the right context, platform capabilities, and controls.
Engineering context
Code, decisions, conventions, and infrastructure, retrieved for each task rather than once per project.
01Need and requirements
Humanissue + acceptance criteria
02Planning and design
Human + agentapproach + affected systems
03Implementation
Agentbranch + change set
04Validation and review
Automated + humanchecks + review record
05Deployment
Policycanary, then production
06Feedback
Teamincidents, metrics, follow-ups
Situations
Recognise the pattern before the tooling
None of these start as an AI problem. They start as work that has to pass through people, repositories, and gates designed for a different volume of change.
01
Agents open changes in minutes. Review, checks, and release were sized for a few pull requests a day, so work accumulates around the people and gates that cannot move faster.
What we look at
We look for avoidable waiting and handoffs, then change the parts of the path that add nothing to the decision.
02
Standards drift between repositories and depend on which reviewer picks up a change. More changes, arriving from more sources, make that variation visible.
What we look at
We define repeatable workflows with shared standards, and where a repository genuinely differs, the variation becomes explicit and justified.
03
Decisions, conventions, and current state live across repositories, documents, and people. An agent that cannot reach them produces work that has to be corrected before review can begin.
What we look at
We identify which sources matter, how agents reach them, and where that context belongs in the workflow.
Services
One produces alignment and a plan. The other turns that direction into a working, validated workflow. A workshop is an optional starting point, not a prerequisite.
Turn an agreed direction into a working, validated workflow, with the platform pieces and controls behind it.
For
Teams that know which workflow to fix and need it working, not just documented.
We work on
You receive
A written proposal defines scope, deliverables, responsibilities, and acceptance criteria.
Understand one workflow, agree on the priority gaps, and choose a practical first pilot.
For
Stakeholders who own one workflow and want agreement before committing to implementation.
We work on
You receive
A workshop produces alignment and a plan. It does not include production implementation.
An example
Imagine a team using a coding agent to add a payment method to checkout. Here is how the workflow could change.
Illustrative scenario—not a customer case study.
Add a payment method to checkout.
Before
The agent starts from a short ticket. Missing requirements surface during review.
With a designed workflow
The team defines the requirements and acceptance criteria before implementation begins.
Before
An engineer finds architecture notes, previous decisions, and repository conventions, then copies them into the agent’s session.
With a designed workflow
Relevant project sources are accessible through the workflow, and the agent is instructed to consult them before making changes.
Before
The reviewer has to ask which checks ran and whether the change meets the team’s standards.
With a designed workflow
Required checks run automatically, with results linked to the pull request for review.
Before
People coordinate approvals and release steps manually. Post-release findings can lose their connection to the original task.
With a designed workflow
Approval rules and release responsibilities are explicit. Deployment results and follow-up findings link back to the work.
We map the workflow with your team, identify the gaps, and design the context access, integrations, checks, and responsibilities it needs. We then help implement and evaluate the agreed changes in a focused pilot.
Our approach
The sequence is deliberately small. Each stage produces something your teams can use without us in the room.
Follow one representative change from requirements through planning, implementation, validation, and release, with the people who own it in the room.
Output · A workflow map that shows where work waits, repeats, or depends on a manual handoff.
With engineering, platform, and security, define the workflow, the context agents receive, responsibilities, and controls appropriate to each type of work.
Output · A designed workflow with named owners, control points, and justified variations where repositories differ.
One team runs the new workflow against a measurable pilot. We compare avoidable waiting, rework, and time to production against the starting point, then iterate.
Output · A running pilot with success measures and evidence of what changed.
Engineering project
Aquifer gives AI agents access to engineering context from project sources through MCP, with source references they can inspect.
Senora builds and uses it in its own work. It covers the context part of an agent workflow: agents retrieve the information, then reason and act with it. Aquifer does not manage the whole development lifecycle, enforce controls, approve changes, or guarantee correct output. Consulting engagements do not require it.
Shaked Braimok Yosef · Founder
Founder
Senora is led by Shaked Braimok Yosef. Her background is platform engineering: infrastructure, developer tooling, and the delivery pipelines teams actually run on.
That is why Senora starts from the pipeline rather than the prompt. Adapting a workflow for agents changes the foundations platform teams already own: the identity an agent acts under, the checks that run on a change, the paths agents and people share, and the tooling that has to be built when nothing suitable exists.
She works directly in repositories, infrastructure, and delivery pipelines, and builds an engineering context tool (Aquifer) in the open. That hands-on view shapes how engagements are scoped: one workflow, small changes to the path, an owner on your side, and a pilot that can be measured before anything is scaled.
Using coding agents—or planning your first pilot? Let’s discuss what you want to improve, what is getting in the way, and a practical place to start.
An introductory conversation to understand your goals and explore whether Senora can help.
Prefer email? shaked@senora.dev