New ways to build software
Develop and compare an alternative architecture, algorithm or agent collaboration method on your own problem.
Cycle output: Prototypes, a comparison with the baseline and conditions for use.
Research laboratory
Develop new approaches
to your challenges.
ALPHA LAB is being built to turn hypotheses into prototypes and test which approaches work in your conditions.
In developmentThe integration package is prepared. A live installation and a complete research cycle have not yet been validated.
The big idea
Organize the creation of new solutions as a managed research cycle.
When familiar methods no longer meet your needs, there is work to do with the unknown: examine the evidence, propose hypotheses, build prototypes and run experiments. We are creating ALPHA LAB to connect these steps and preserve what each attempt teaches you.
The research cycle
From a question to a new approach and its evaluation.
Alpha Agent receives the objective and organizes the work. The laboratory is designed to connect research, development and evaluation. You set the boundaries and decide what to implement.
This is the intended process. A complete run still needs to be demonstrated on the first task.
- 01
Frame the question
What needs to change? What would count as an improvement over the current approach?
- 02
Examine the foundations
Review sources, existing solutions, constraints and initial data. Separate evidence from assumptions.
- 03
Propose hypotheses
Explore several ways to resolve the contradiction. State each mechanism and the conditions under which it could fail.
- 04
Build prototypes
Express the ideas in code, a process model or a testable mockup. Set up comparable conditions.
- 05
Run experiments
Compare prototypes with the baseline and record observations, errors and limitations. Repeat the checks that matter.
- 06
Preserve what you learn
Collect the evidence for the next decision: develop the approach, revise the hypothesis or stop this line of inquiry.
Research directions
Where a ready-made answer is not enough.
Examples for future pilots. Each starts with a specific question and criteria chosen before the work begins.
Applied research
Turn an assumption about data, a model or a process into an experiment that can be repeated.
Cycle output: An experiment plan, observations and a conclusion with stated limits.
Rethinking familiar processes
Rethink a familiar process and explore new approaches to its constraints and contradictions.
Cycle output: A testable model of a new process and evidence for the next step.
Scientific foundations
A scientific approach to complex problems and contradictions.
ALPHA LAB is being designed to explore new approaches with attention to evidence, constraints and uncertainty. The depth of research depends on the task, and the laboratory's work still needs to be validated in practice.
Working with contradictions
Exploring solutions to problems where important requirements conflict.
Understanding constraints
Understanding what limits the result and where there is room for a new approach.
Evaluating hypotheses
Assessing ideas through observable results and the conditions in which they may be useful.
Critical evaluation
Attention to alternatives, uncertainty and the limits of each conclusion.
Research outputs
Materials you can build on.
The laboratory is designed to leave a foundation for the next decision. A hypothesis that is not supported can still be useful when the conditions, observations and remaining questions are preserved.
ALPHA LABResearch dossier contents
- Initial question, criteria and constraints
- Sources and a map of assumptions
- Hypotheses and the reasons for choosing them
- Prototype code and execution conditions
- A record of attempts, measurements and errors
- Conclusions, limitations and the next step
These are the intended outputs. A finished task does not mean that a scientific conclusion has been accepted or novelty established.
Within the Alpha ecosystem
One laboratory. Familiar ways to direct it.
ALPHA LAB is conceived as a research laboratory directed by Alpha Agent. Connections from Claude and Codex are intended to provide access to the same working environment.
- Alpha AgentThe primary coordinator: receives the objective, assigns laboratory tasks and returns the results to you.
- ALPHA LABThe research environment: hypotheses, prototypes, experiments and materials ready for review.
- YouSet the objective and permitted actions, evaluate the evidence and decide what to implement.
Plugins for Alpha Agent, Claude and Codex are being prepared. Model access, permissions and a verification run are configured separately. Compatibility with live clients has not yet been validated.
Meet Alpha AgentThe first step
Start with a question worth investigating.
Choose one task where the current approach limits your results. These three points help prepare it for the research cycle.
Discuss a research questionDiscussing a task does not automatically start research. Scope and environment readiness are established separately.
- 01
What would you like to change?
Describe the current approach and its specific limitation.
- 02
How will you measure the result?
Choose an observable criterion and a way to compare it with what already works.
- 03
What are the boundaries?
Specify the available data, time, budget and actions that require your decision.
Questions and answers
Before you begin.
Is ALPHA LAB running already?
The integration package is prepared. A live installation and a complete research cycle have not yet been validated. This page describes the purpose and intended process.
Is it a product or a module?
ALPHA LAB is positioned as a research laboratory. A module connection within Alpha Agent is planned. Plugins for Claude and Codex are planned as additional ways to direct the same laboratory.
Does the laboratory guarantee a new invention?
No. It is being created to organize inventive work. Usefulness, reproducibility and scientific novelty require separate evaluation. A hypothesis may not be supported by an experiment.
Do I need to run a model locally?
A model can be connected through an API. The execution environment and model are configured separately, and resource requirements depend on the research task.
Who decides whether a result can be implemented?
The task owner. The laboratory is intended to provide results, evidence and limitations. Changes to working systems require a separate decision.