Give ideas a fair test.
Start with a question worth answering. Define the outcome before asking agents to do the work.
An AI marketing engine · In development
Find what works.Put it to work.
Turn promising marketing ideas into tactics worth repeating. TacticLoop is being built to help small teams test, learn, and give AI agents a clear plan to execute. You set the direction. Every cycle informs the next.
Made for independent founders and small teams.
A system for the next good move.Concept illustration
Marketing that learns, with you in control.
Test ↗ Measure ↗ Improve ↗ Repeat
01 / The purpose
Every campaign should leave you with more than content.
A clearer audience. A better message. A tactic you can use again.
TacticLoop is designed to connect the whole cycle: a promising idea, a focused test, an approved plan, and the evidence to decide what comes next.
The ambition is simple: make your next marketing decision better informed than the last.
Keep the useful learning.
Carry evidence, context, and decisions into the next cycle. Make each experiment easier to build on.
Make good tactics repeatable.
Turn an approved approach into a clear sequence of work, with boundaries your agents can follow.
02 / Meet the engine
A little more learning.
Every time around.
Explore the intended workflow. Four connected stages turn a marketing question into a more informed next move.
Learn / A focused hypothesis
Make the first step clearer.
Imagine a planning app whose new users need a better starting point. The team wants to understand what helps them begin.
The questionWould a short walkthrough help people complete their first useful action?Next move: compare two ways to explain the same workflow.
Start with a question the evidence can answer.
Prove / A bounded experiment
Agree on what success means.
Compare two explanations. Decide the measurement window and comparison method before the experiment begins.
TACTIC AAn illustrated getting-started guide
TACTIC BA short product demonstration
The outcome to measureCompletion of the first meaningful product action.
Run / An approved protocol
Give agents a clear brief.
Define the work, the destination, and the boundaries. A useful tactic becomes a plan that can be repeated.
Example permissions, not a connection to a live account.
Refine / An evidence-led decision
Make the next move wiser.
Review visits, meaningful product use, and the quality of the comparison. Choose what the evidence can support.
A principle of the loopInconclusive results stay inconclusive.Preserve the finding. Improve the next question.
Illustrative workflow · A fictional product example · No live accounts or performance results
Small experiments. Useful evidence. A better next step.03 / Deliberate by design
Your ambition.
Your boundaries.
Set the direction. Keep your hands on the controls. The engine is being designed around what agents may say, where they may act, what they may spend, and when they need a review.
A defined scope
Give each tactic a clear objective, approved claims, and permitted destinations.
Finite budgets
Set limits for spend and work. Define where an agent must stop and ask.
A trail you can follow
Connect an action to its plan, permission, and result. Keep decisions understandable.
Room to intervene
Pause future work and review pending actions as circumstances change.
These are the principles guiding the product currently in development.
04 / Built with small teams in mind
For people building
something of their own.
Start with one clear outcome and a manageable experiment. Expand when the evidence gives you a reason.
Independent founders
Make focused progress with the time and resources you have.
Small product teams
Bring message, experiment, and product outcome into the same conversation.
Teams working with AI agents
Give capable agents a repeatable brief and a defined boundary for action.
05 / A few useful answers
Clarity from
the beginning.
Where is TacticLoop today?
TacticLoop is in early development. Its product direction and operating architecture are defined; production connections and customer pilots are still ahead. This website introduces the intended product and an illustrative workflow.
What would agents be able to do?
The intended engine connects research, experiment planning, content preparation, approved execution, and measurement. Actions depend on the connected service, its supported permissions, and the scope you authorize. A new claim, destination, budget, or permission may require another review.
How will it decide whether a tactic works?
The plan is to define meaningful outcomes before an experiment begins, then assess both results and evidence quality. Outcomes might include first useful product use or continued use. A promising signal can justify another test; it is not automatically proof that the tactic caused a result.
Is the example connected to real marketing accounts?
No. The four-stage walkthrough is an interactive illustration using a fictional product. It does not publish content, connect accounts, or display measured performance.
Who is the first version for?
The initial focus is independent founders and small software teams. A narrow pilot is the intended starting point: one product, a small set of permitted channels, explicit limits, and evidence that can guide the next release.