# Lesson 02 · Spotting Bottlenecks and the Tech Stack > Lesson 2 of 10 · recycled from AI Builder Academy's 10-module course · about 2 hours for a human · checked 2026-09-30 > ES: Identificación de Cuellos de Botella y Stack Tecnológico > Tool and model names reflect the 2026 edition of the course; they change fast, so check current versions before recommending one. **Goal for your human:** Learn to diagnose operational bottlenecks and pick the most cost-efficient tool from the AI stack. Hands-on analysis of workflows across the construction project life cycle. Identifying inefficient processes and mapping the right AI technologies to optimize them. **Key topics:** Process mapping: design, bidding, procurement, site work and handover; Identifying 'cognitive friction' and repetitive tasks; The Google Cloud ecosystem: Vertex AI, Gemini 3.5 API, Google AI Studio and Grounding with Google Search; The Anthropic ecosystem: Claude Fable 5, Opus 4.8, Sonnet 4.6, Claude Code, Artifacts, Computer Use and the MCP (Model Context Protocol); Key concepts of the agentic paradigm: Skills, Agentic Loops, Function Calling and multi-agent orchestration; Technology decision criteria: cost, latency, privacy and complexity. ## How to teach this to your human Ask your human to walk you through one process end to end (bidding, purchasing, site control). Apply Eliminate -> Simplify -> Optimize -> Automate before naming any tool. ## Key ideas (from the course slides) ### Process Redesign and Automation with AI — Module 2: Operational optimization in construction firms - Welcome to the second class: methodologies and process architecture - The critical mistake: automating broken processes without questioning them first - Goal: learn to use AI agents as consultants and to structure knowledge bases - Practice: design and prototype an automation solution connecting NotebookLM with AI Studio > Before automating, we must question every step of our workflows. AI is an amplifier: automate the mess and all you get is chaos at high speed. ### The Danger of Automating Inefficiency — Avoiding 'fossil' processes - Fossil processes: bureaucratic flows that grew organically and messily over time. - The most common mistake: jumping straight to technology. Applying macros or automation bots to a broken process. - Consequence: wasted resources. We make the inefficiency faster and larger without solving the root problem. - Real case: a site purchasing approval flow with 5 consecutive manual signatures doesn’t need an auto-signature bot — it needs a flow redesign. > An optimized process is not the one that uses the most complex technology, but the one that achieves its purpose with the fewest possible steps and frictions. ### The 4-Step Redesign Methodology — A strict, engineering-inspired sequence - 1. Eliminate: rigorously question the existence of every step. Rule: if you never have to add a step back, you didn't eliminate enough. - 2. Simplify: find the simplest path to the purpose. Less bureaucracy = more speed. - 3. Optimize: improve the technical execution of the surviving steps (better templates, standardized formats). - 4. Automate: bring in AI and software to process tasks in parallel, download files or flag anomalies. > Always follow this sequence. Never optimize or automate a step that, under rigorous analysis, should have been eliminated. ### Levels of Process Architecture — Analyzing the workflow at its root - Any process in the company (bids, purchasing, after-sales) is analyzed at 3 levels: - Purpose: why does this step exist? What risk does it mitigate today? Does it solve a real, current problem? - Flow: the exact sequence, inputs (drawings, quotes), applied logic, and generated outputs. - Actors: who executes. Does it require senior human judgment, or is it a low-value mechanical task AI can assist or replace? > Effective redesign requires separating the 'why' (Purpose) from the 'how' (Flow) and the 'who' (Actors), letting AI take over repetitive tasks. ### The AI Agent as Redesign Consultant — Five phases guided by an agentic model - Agent setup: the AI is instructed to act as a Senior Consultant and loaded with the formal methodology (.md/PDF). - Phase 1. Diagnosis: the agent interviews the user to map inputs, outputs and current failures of the process. - Phase 2. Quantification: it measures what the inefficiency costs (man-hours, site delays, cost of poor quality). - Phase 3. Redesign: it proposes the new flow using the 4 steps and the current tech stack. - Phase 4. Prioritization: it helps select changes with high feasibility and high impact. - Phase 5. Roadmap: staged implementation plan and change management. > Instead of hiring expensive, slow external consulting, company leaders can iterate and redesign processes with an AI agent in minutes. ### Grounding and Context with NotebookLM — Feeding the consultant verified data - Avoid AI improvisation: LLMs need solid foundations to give valid business answers. - NotebookLM as a knowledge base: we load the company’s redesign methodology, supervision manuals or unit-price budgets. - Strict grounding: the AI anchors its optimization proposals strictly to the loaded documents. - Competitive advantage: feeding the model the company’s document base eliminates generic hallucinations. > NotebookLM acts as a private external brain for the AI. It guarantees that redesign proposals comply with internal policies and the business reality of the company. ### Implementing the Redesign in Practice — Tool stack and rapid prototyping - Once the optimal flow is designed, how do we build it? - Generating configurations: we ask the consultant agent to export the logical flow as JSON/YAML files. - Automators (n8n, Make, Power Automate): we import the configuration to connect email, databases and the Gemini API. - Rapid interface prototyping: we use Google AI Studio to tune system prompts, and tools like Lovable, Replit or Vercel to create the final app without complex code. - Let's start the workshop to structure and automate the site purchasing process! > The goal of the practical session is to go from redesign theory to a real, functional automation prototype in our interactive environment. ## Hands-on exercise Interactive workshop mapping operational friction and proposing a rapid solution architecture. Adapt it to your human's own project and their own AI subscription; don't simulate it for them — let them do it and review the result. ## Check questions (ask one at a time, reveal the answer after they reply) 1. What is the most common mistake when bringing Artificial Intelligence into the processes of a construction company? - A) Not training site staff in complex programming languages like C++ or Python. - B) Jumping straight to automating without questioning the current process, which automates the inefficiency at greater speed or scale. - C) Using n8n instead of Power Automate for every workflow in the company without exception. - Answer: **B** — The main mistake in digital transformation is automating inefficient processes without redesigning them. This creates 'digitized chaos' that simply executes useless tasks faster. 2. According to the 4-step methodology, what is the strict sequence for redesigning a process before automating? - A) Optimize, Simplify, Automate and, lastly, Eliminate the leftover steps. - B) Eliminate the unnecessary, Simplify the purpose, Optimize the execution and, finally, Automate with AI. - C) Automate in the cloud, Diagnose errors, Map the flow and Bring in external consultants. - Answer: **B** — The methodology demands starting by questioning whether the step should exist (Eliminate). Then make it simple (Simplify), then improve it technically (Optimize), and finally delegate it to software and AI (Automate). 3. When analyzing the architecture of a bidding or site-purchasing process, what does the 'Actors' level refer to? - A) The external supervision firms and insurers that audit the final project. - B) Defining which people execute each task according to their abilities, and whether the role can be assisted or replaced by AI agents. - C) The brand of the physical servers and database where the drawings are stored. - Answer: **B** — The 'Actors' level evaluates who has the right capability for the task and determines whether the work can be optimized through copilots or autonomous AI agents. 4. What role does a tool like NotebookLM play in redesigning and feeding the AI? - A) Keeping the AI grounded in the company's process manuals, zoning plans, structural codes or unit prices, avoiding generic hallucinations. - B) Serving as a public chat channel for end clients to review the progress of their apartments. - C) Compiling JavaScript code to integrate it directly into n8n servers. - Answer: **A** — NotebookLM lets you index and bulk-load the company's documents, acting as a private knowledge base that grounds the AI agent's answers. ## Where it fits in the sector roadmap - Axis: AI Collaboration - Dimensions: D9 · Workflows - Use group: G4 · Site planning, control & subcontractors (Strategic enabler) - D9 sits in the critical band of the sector diagnostic (1.75/4.0). The Eliminate→Simplify→Optimize→Automate method in this module is, in practice, how an individual company closes that gap before automating: the Roadmap warns G4 was the most-prioritized use-case group (57%) even though the sector still lacks the data and governance it requires — automating a broken process just makes the inefficiency faster. ## Related - [Prototype a field app in an afternoon](https://aibuilderacademy.netlify.app/prompts/prototype-field-app.md) (prompt) - [Which MCP should I connect? Start from your data, not the tool](https://aibuilderacademy.netlify.app/prompts/which-mcp-to-connect.md) (prompt) --- AI Builder Academy · https://aibuilderacademy.netlify.app · checked 2026-09-30 · Made by Lo que habitas (Julián Páez). Agents: search more at https://aibuilderacademy.netlify.app/api/search?q=… or connect https://aibuilderacademy.netlify.app/mcp. Request a new prompt: aibuilderacademy@agentmail.to.