First Principles AI Workflow

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Your language must be precise, analytical, and devoid of colloquialisms or speculative commentary. All outputs must adhere strictly to the requested JSON format, providing structured, actionable intelligence. The objective is to function as a specialized cognitive unit within a larger analytical engine, not as a conversational assistant.\";\n\nconst DECONSTRUCTOR_PROMPT = `\nYou are 'Agent Deconstructor'. Your function is to analyze a user-submitted problem statement and break it down into its most fundamental components and invariable truths.\n\nAnalyze the following problem: \"{ProblemStatement}\"\n\nYour response MUST be a single, minified JSON object with two keys:\n1. \"components\": An array of strings, where each string is a core, irreducible element of the problem.\n2. \"invariables\": An array of strings, where each string is a fundamental truth or constraint (e.g., laws of physics, core human needs, mathematical constants) relevant to the problem domain.\n\n${AGENT_PERSONA_GUIDE}\n`;\n\nconst CONTRARIAN_PROMPT = `\nYou are 'Agent Contrarian'. Your function is to challenge the outputs of the Deconstructor agent. You will be given a list of components and invariables. For each, identify a core, unstated assumption and formulate a precise interrogative question to challenge its validity.\n\nAnalyze the following:\n- Components: {Components}\n- Invariables: {Invariables}\n\nYour response MUST be a single, minified JSON object with one key, \"challenges\". This key must contain an array of objects, each with two keys:\n1. \"assumption\": A string stating the implicit assumption being made.\n2. \"interrogation\": A string posing a question that tests the limits or validity of the assumption.\n\n${AGENT_PERSONA_GUIDE}\n`;\n\nconst SYNTHESIZER_PROMPT = `\nYou are 'Agent Synthesizer'. Your function is to reconstruct a novel solution from first principles, using the outputs from the Deconstructor and Contrarian agents. Your solution must be expressed as a transfer function using lambda calculus notation.\n\nReference Material:\n- Original Problem: \"{ProblemStatement}\"\n- Deconstructed Components: {Components}\n- Challenged Assumptions: {Challenges}\n\nYour response MUST be a single, minified JSON object with one key, \"reconstruction\". This key must contain an object with two keys:\n1. \"description\": A concise, one-sentence summary of the new approach.\n2. \"transfer_function\": A string representing the solution as a lambda expression. The function should take the problem's fundamental components as inputs and produce a new output. Example: \"λ(input_A, constraint_B) => { return new_approach_combining_A_and_B; }\"\n\n${AGENT_PERSONA_GUIDE}\n`;\n\nconst STRATEGIST_PROMPT = `\nYou are 'Agent Strategist'. Your function is to devise a verification and testing plan for the novel solution proposed by the Synthesizer. Each verification step must be framed as a transfer function using lambda calculus notation.\n\nAnalyze the following proposed solution:\n- Solution Description: \"{SolutionDescription}\"\n- Solution Function: \"{SolutionFunction}\"\n\nYour response MUST be a single, minified JSON object with one key, \"verification_plan\". This key must contain an array of objects, each with two keys:\n1. \"experiment\": A string describing a specific test or experiment to validate one aspect of the solution.\n2. \"validation_function\": A string representing the test as a lambda expression. The function should take the output of the proposed solution and return a success or failure state with a rationale. Example: \"λ(solution_output) => { if (solution_output.metric > threshold) return { valid: true }; else return { valid: false, reason: 'Metric below threshold' }; }\"\n\n${AGENT_PERSONA_GUIDE}\n`;\n\nconst ORCHESTRATOR_PROMPT = `\nYou are 'Agent Orchestrator'. Your function is to perform a meta-analysis of the entire problem-solving workflow. Review the inputs and outputs of all agents to provide a final assessment.\n\nWorkflow Data:\n{WorkflowData}\n\nYour response MUST be a single, minified JSON object with two keys:\n1. \"assessment\": A string classifying the final solution (\"INNOVATIVE\", \"INCREMENTAL\", \"IMPRACTICAL\").\n2. \"summary\": A one-sentence executive summary explaining the assessment and the core insight derived from the first-principles process.\n\n${AGENT_PERSONA_GUIDE}\n`;\n\n// --- Type Definitions ---\n\ninterface JobState {\n status:\n | \"pending\"\n | \"deconstructing\"\n | \"challenging\"\n | \"synthesizing\"\n | \"strategizing\"\n | \"analyzing\"\n | \"complete\"\n | \"error\";\n error?: string;\n problemStatement: string;\n workflowData?: {\n components?: string[];\n invariables?: string[];\n challenges?: { assumption: string; interrogation: string }[];\n reconstruction?: { description: string; transfer_function: string };\n verification_plan?: { experiment: string; validation_function: string }[];\n final_analysis?: { assessment: string; summary: string };\n };\n}\n\n// --- CORE AI & WORKFLOW LOGIC ---\n\nconst openai = new OpenAI();\n\nasync function callAI(\n promptTemplate: string,\n replacements: Record,\n): Promise {\n try {\n let finalContent = promptTemplate;\n for (const key in replacements) {\n finalContent = finalContent.replace(\n new RegExp(`\\\\{${key}\\\\}`, \"g\"),\n replacements[key],\n );\n }\n\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [{ role: \"user\", content: finalContent }],\n response_format: { type: \"json_object\" },\n });\n\n const responseContent = completion.choices[0].message.content;\n const jsonMatch = responseContent.match(/\\{[\\s\\S]*\\}/);\n if (!jsonMatch) {\n throw new Error(\"AI response did not contain a valid JSON object.\");\n }\n return JSON.parse(jsonMatch[0]);\n } catch (error) {\n console.error(\"AI call failed:\", error);\n throw new Error(\n `AI agent failed to generate a valid response. Details: ${error.message}`,\n );\n }\n}\n\nasync function runWorkflowInBackground(\n jobId: string,\n problemStatement: string,\n) {\n const updateState = async (\n status: JobState[\"status\"],\n data: Partial = {},\n ) => {\n const currentState: JobState = await blob.getJSON(jobId) ||\n { problemStatement };\n await blob.setJSON(jobId, {\n ...currentState,\n status,\n workflowData: { ...currentState.workflowData, ...data },\n });\n };\n\n try {\n // Stage 1: Deconstructor\n await updateState(\"deconstructing\");\n const deconstructorResult = await callAI(DECONSTRUCTOR_PROMPT, {\n ProblemStatement: problemStatement,\n });\n await updateState(\"deconstructing\", { ...deconstructorResult });\n\n // Stage 2: Contrarian\n await updateState(\"challenging\");\n const contrarianResult = await callAI(CONTRARIAN_PROMPT, {\n Components: JSON.stringify(deconstructorResult.components),\n Invariables: JSON.stringify(deconstructorResult.invariables),\n });\n await updateState(\"challenging\", { ...contrarianResult });\n\n // Stage 3: Synthesizer\n await updateState(\"synthesizing\");\n const synthesizerResult = await callAI(SYNTHESIZER_PROMPT, {\n ProblemStatement: problemStatement,\n Components: JSON.stringify(deconstructorResult.components),\n Challenges: JSON.stringify(contrarianResult.challenges),\n });\n await updateState(\"synthesizing\", { ...synthesizerResult });\n\n // Stage 4: Strategist\n await updateState(\"strategizing\");\n const strategistResult = await callAI(STRATEGIST_PROMPT, {\n SolutionDescription: synthesizerResult.reconstruction.description,\n SolutionFunction: synthesizerResult.reconstruction.transfer_function,\n });\n await updateState(\"strategizing\", { ...strategistResult });\n\n // Stage 5: Orchestrator\n await updateState(\"analyzing\");\n const finalState: JobState = await blob.getJSON(jobId);\n const orchestratorResult = await callAI(ORCHESTRATOR_PROMPT, {\n WorkflowData: JSON.stringify(finalState.workflowData, null, 2),\n });\n await updateState(\"complete\", { final_analysis: orchestratorResult });\n } catch (error) {\n console.error(`Workflow failed for job ${jobId}:`, error);\n await blob.setJSON(jobId, {\n status: \"error\",\n problemStatement,\n error: error.message,\n });\n }\n}\n\n// --- HTML & FRONTEND ---\n\nfunction generateHtml(sourceUrl: string): string {\n return `\n \n \n \n \n \n First Principles AI Workflow\n \n \n \n \n \n \n

\n \n\n

\n \n

\n\n

\n \n

1. Agent Deconstructor

\n Pending\n

\n\n

2. Agent Contrarian

\n Pending\n

\n\n

3. Agent Synthesizer

\n Pending\n

\n \n

4. Agent Strategist

\n Pending\n

\n\n

\n\n \n \n \n `;\n}\n\n// --- HTTP REQUEST HANDLER ---\n\nexport default async function (req: Request): Promise {\n const url = new URL(req.url);\n const path = url.pathname;\n const headers = { \"Content-Type\": \"application/json\" };\n\n try {\n if (req.method === \"POST\" && path.endsWith(\"/start\")) {\n const { problem } = await req.json();\n if (\n !problem || typeof problem !== \"string\" || problem.trim().length === 0\n ) {\n return new Response(\n JSON.stringify({ error: \"A valid 'problem' string is required.\" }),\n { status: 400, headers },\n );\n }\n\n const jobId = nanoid();\n const initialState: JobState = {\n status: \"pending\",\n problemStatement: problem,\n };\n await blob.setJSON(jobId, initialState);\n\n runWorkflowInBackground(jobId, problem);\n\n return new Response(JSON.stringify({ jobId }), { status: 202, headers });\n }\n\n if (req.method === \"GET\" && path.endsWith(\"/status\")) {\n const jobId = url.searchParams.get(\"jobId\");\n if (!jobId) {\n return new Response(\n JSON.stringify({ error: \"A 'jobId' query parameter is required.\" }),\n { status: 400, headers },\n );\n }\n\n const state: JobState | undefined = await blob.getJSON(jobId);\n if (!state) {\n return new Response(\n JSON.stringify({ status: \"error\", error: \"Job not found.\" }),\n { status: 404, headers },\n );\n }\n\n return new Response(JSON.stringify(state), { headers });\n }\n\n if (req.method === \"GET\") {\n const sourceUrl = `https://${url.hostname}${\n url.pathname.substring(0, url.pathname.lastIndexOf(\"/\")) || url.pathname\n }`;\n return new Response(generateHtml(sourceUrl + \"/\"), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n }\n\n return new Response(JSON.stringify({ error: \"Not Found\" }), {\n status: 404,\n headers,\n });\n } catch (error) {\n const errorMessage = error instanceof Error\n ? 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