This New Way

• The Future of Engineering Ops: AI Agents That Listen, Write & Ship with Alexandra Sunderland

  In this episode, Alexandra Sunderland (VP of Engineering at Fellow) pulls back the curtain on how she runs engineering with agentic workflows that actually move the needle: background coding agents in Cursor that fix bugs while she’s in meetings, Claude + MCPs to query Linear and auto-generate reports in seconds, and Zapier pipelines that turn meeting transcripts into daily briefs, real-time project risk pings, sales insights, and even 1:1 growth trackers. The theme: make conversations computable, specialize agents narrowly, and wire every tool together so ops happen while you sleep.Timestamps1:11 — Background: 13+ yrs with Aydin; author of Remote Engineering Management.2:13 — What is an “agent”? Alexandra’s practical definition (automation + LLM).3:39 — Why specialized agents beat general ones (Sept 2025 reality check).5:25 — Cursor background agents via Slack VIP notifications—coding while she’s away.8:00 — Hackathon: hand-built dev productivity dashboard vs. Claude + Linear MCP.10:38 — Why use Claude here instead of Cursor: downloadable PDFs & exploratory insights.13:03 — Interface shift: logging into Linear/GitHub less; notify via Slack instead.14:21 — Plan: live workflows that leaders can copy.15:31 — Workflow #1: Daily Brief in Zapier (9:00 a.m. trigger → transcripts → CoS-style digest).18:00 — Slack example of the generated daily brief.20:22 — Workflow #2: Project Meeting Insights—real-time blockers & cross-team risks.22:00 — Prompting style (“best VP of Eng in the world”) and why it helps.26:40 — Idea: an “Alexandra agent” that drafts her responses.27:59 — Workflow #3: Sales call mining → bug/feature requests for Eng.29:14 — Next step: Cursor agents created via API—fixes ready for human review minutes after calls.30:23 — Rolling Cursor to product & success; non-engineers leverage code context.31:16 — Auto-drafting help center docs with Cursor that can browse.32:34 — Future: docs auto-update—or vanish into on-demand LLM answers.34:52 — Workflow #4 (WIP): 1:1 growth tracker—extract coaching, strengths, feedback into a living doc.37:41 — Sales coaching automation: enforce key phrases/objection handling.38:10 — Playbook: start with simple “yesterday’s conversations → insights,” then stack.39:24 — Next 12 months: tools connecting to each other, patterns across datasets.Tools & Technologies Mentioned (with quick notes)Cursor — AI-powered code editor with background agents (cloud-run) and Slack integration for async coding and fixes.Cursor Background Agents API — Programmatically spin up agents to implement bug fixes/features for later human review.Slack (VIP Notifications) — Marking the Cursor app as VIP ensures agent updates punch through Do Not Disturb.Claude — LLM used with MCPs to query data sources (e.g., Linear), generate PDFs, surface trends, and build ad-hoc reports.MCP (Model Context Protocol) — Standard to connect LLMs to tools/data (e.g., Linear) for live, permissioned operations.Linear — Issue/project tracker; source for ticket analytics (resolution rates, triage time, stage durations).Zapier — No-code automations; schedules, filters, formats, makes API calls, and runs AI by Zapier LLM steps.Fellow.ai — AI meeting assistant capturing summaries, actions, decisions; acts as an “AI chief of staff” across meetings.GitHub — Code hosting referenced as a UI Alexandra now visits less thanks to agentic workflows.Google Docs / Notion / Wiki — Destinations for auto-appending 1:1 growth notes and team principles.APIs (custom + vendor) — Zapier “Webhooks by Zapier”/custom API calls used to fetch transcripts and trigger agents.Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

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• How a 4-Person Team Runs a 7-Figure Business with AI | Emil & Cassy Aite

  In this episode, Aydin chats with brothers Emil and Cassy—founders behind Hoppier (snack stipends for teams) and Postbeam (an AI-native LinkedIn content engine). They show how transcripts, voice interfaces, and AI browsers can 10× content output and product velocity for small teams. Demos include: turning transcripts into LinkedIn posts, Postbeam’s “Marv” voice interview, Vercel v0 mockups, and Perplexity’s Comet browser agent. The theme: tiny teams, mighty outcomes—when AI is baked into every workflow.Timeline & Timestamps01:08 – Hoppier origin: ~1,200 customers, profitable, still founder-run.03:57 – Why transcripts are gold for creating unlimited content.05:06 – Demo: pulling a podcast transcript into Claude → strong LinkedIn post hooks.08:55 – Volume matters: consistency wins; learning from creators like Pablo.11:15 – Remix vs. original insights: two formulas for content that works.14:38 – From process to product: Postbeam lands early paying customers.16:26 – Inside Postbeam: sources, remixing, images, and multi-team member voices.18:33 – Demo: Marv voice feature interviews you to capture authentic tone.24:21 – Building with AI: using Vercel v0 for rapid UI mockups and team feedback.29:16 – Aydin’s day job plug: Fellow.ai meeting assistant.31:36 – Replit vs. V0 vs. Lovable: pros, cons, and caution for prod-grade apps.35:58 – Comet browser demo: finding Toyota RAV4s on Marketplace with AI.42:42 – Tiny but mighty: Postbeam (2 founders + Gen Z cousin) and Hoppier (7-figure biz with 4 ppl).Tools & Technologies MentionedClaude (Anthropic) — Generates LinkedIn posts from transcripts.ElevenLabs / YouTube Transcript Tools — For pulling transcripts.Postbeam — AI LinkedIn content engine.Marv (inside Postbeam) — Voice interview AI to capture tone.Vercel v0 — Natural language → React UI mockups.Replit / Lovable / Cursor — AI coding platforms, with tradeoffs.Perplexity’s Comet Browser — Agentic browser for automated browsing.Whisper Flow — Voice-first workflow automation.Fellow.ai — AI meeting assistant.Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

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• AI Teammates that Write Briefs, Draft Blogs & Keep Projects on Track with Marquis Murray

  Host Aydin Mirzaee welcomes Marquis Murray, productivity consultant and YouTuber, to share how AI agents are transforming day-to-day work. Marquis walks through live demos connecting Claude to Asana via MCP to auto-build projects from transcripts, generate executive-ready status PDFs, and create “AI teammates” in Asana that triage requests, draft briefs, write emails/blogs, and route approvals—keeping humans in the loop. Once you see it, you won’t go back to manual setup.Timestamps0:06 – Why manual project planning is over; AI compresses weeks into minutes.0:17 – Introducing Marquis Murray.0:43 – Starting the YouTube channel during lockdowns; documenting Asana learnings.2:06 – From corporate to consulting; helping teams adopt Asana, HubSpot, Zoom, Slack.4:05 – Making companies more productive with AI and integrations.4:53 – Today’s plan: Claude + Asana + agents.6:06 – Using Claude as a “central AI” via MCP.8:17 – Building a Customer Appreciation Event project in Asana directly from Claude.12:20 – Custom fields/sections: what connectors can and can’t create.13:06 – Finished example: phases, tasks, owners, dates.14:05 – Feeding transcripts and docs to generate realistic demo projects.19:05 – “If you’re not doing this yet, start today.”19:42 – Pulling Asana status into Claude and exporting a polished PDF.23:34 – Exec-friendly reports: progress bars, metrics, priorities.24:50 – Asana AI Studio: agents as virtual teammates.27:23 – Auto-correcting human errors: naming, missing info, duplicates.29:02 – Agents rename tasks, create briefs, draft assets.35:42 – Agents gatekeep incomplete requests; ask for specifics.37:13 – AI-generated campaign brief, email, and blog drafts.39:08 – Human-in-the-loop approvals before going live.43:01 – Triage demo: vague video request → structured follow-ups.45:25 – Auto-created subtasks to collect missing details.46:33 – “Easy mode” for building agents with natural language.47:03 – Marquis’s wish: a true AI chief of staff that restructures your day.48:56 – Where to find Marquis’s tutorials; wrap-up.Tools & Technologies MentionedAsana — Project management platform; AI Studio builds rule/LLM agents (“teammates”).Claude (Anthropic) — AI assistant used for brainstorming, MCP connections, summaries.Perplexity — AI search and research assistant.HubSpot / Salesforce / Jira — CRM/dev tools commonly integrated with Asana workflows.Zoom & Slack — Core collaboration stack surfaced during remote shift.MCP (Model Context Protocol) — Lets LLMs securely interact with external tools like Asana.Fellow.ai — AI meeting assistant for accurate summaries, action items, and insights.Google Drive, Gmail, Calendar, Canva — Connected apps Claude can use to orchestrate work.Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

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• How a Chief Engineering Officer Automates Customer Prep, Scheduling & Reports with AI | Ali Pourshahid of Solace

  In this episode of This New Way, Aydin sits down with Ali Pourshahid, Chief Engineering Officer at Solace, to explore how he’s woven AI into his daily routines as a technology executive. Ali shares real demos of how he uses Solace’s Agent Mesh and other AI tools to:Generate security-focused slide decks from Confluence in minutesSchedule a 12-person leadership offsite without lifting a fingerTransform messy Word reports into polished heat maps for government updatesAutomate customer support workflows across Jira, CRM, and internal systemsAli also breaks down how Solace is productizing their internal AI system, why agent-to-agent communication (A2A) is critical, and how to build a culture of experimentation with “AI champions” inside your company.This is a masterclass in how executives can stop just “keeping up” with AI—and instead lead the charge.Timestamps0:58 – What is Solace and Ali’s role as Head of Engineering2:09 – Ali’s daily “AI deep hour” and why he treats it like a workout3:19 – Prepping for a customer security call with AI + Confluence5:14 – Auto-generated sequence diagrams and value slides in minutes9:48 – Using Microsoft Copilot to instantly format professional slides13:35 – AI as an executive assistant: scheduling a 12-person workshop17:01 – Turning unstructured Word reports into project heat maps20:07 – Building an AI champions group and lightning talks at Solace25:05 – Solace Agent Mesh: event-driven architecture for agents29:01 – Live demo: Automating Jira support tickets with agent workflows33:33 – Scaling digital employees with orchestrator agents37:08 – Why evals are critical for testing and deploying AI agents39:05 – Ali’s habit: always ask “How can I do this better with AI?”40:08 – What excites Ali most about AI in the next yearTools & Technologies Mentioned:Solace Agent Mesh – Multi-agent orchestration platform built by SolaceConfluence – Wiki where AI pulls technical details for slide prepClaude & ChatGPT – LLMs used for connecting to internal toolsMCP (Model Context Protocol) – Framework for securely connecting AI to enterprise dataMicrosoft Copilot – AI inside PowerPoint, Excel, and other Office toolsMermaid – Visualization tool for generating diagrams and heat mapsA2A Protocol (Agent-to-Agent) – Open standard for agent communication donated by GoogleSubscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

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• How Motive Uses 1,000+ AI Agents to Boost Productivity by 50% with Maddie Engelmeier

  In this episode of This New Way, Aydin sits down with Maddie Engelmeier, AI leader at Motive, to dive deep into how her team is transforming employee productivity with AI. Motive has set an ambitious company-wide goal: boost productivity by 50%. Maddie shares the three-tier strategy behind this initiative, showcases real AI agents in action—from self-assessment tools to executive account summaries—and explains how Motive fosters an AI-native culture across 100,000 customers and 1.3 million drivers.From using Glean to power performance reviews, to leveraging Notebook LM for instant enablement videos, Maddie gives a behind-the-scenes look at how AI is not just saving time but elevating effectiveness across the company.Timestamps0:00 – Setting the stage: Motive’s ambitious 50% productivity goal1:04 – Maddie introduces Motive and her role leading AI initiatives3:12 – The three-tier AI adoption framework (democratization, automation, transformation)6:51 – Why Motive adopted Glean and how it evolved from search to an agentic platform8:08 – Demo: Self-assessment agent for performance reviews13:06 – How Glean pulls from Slack, Drive, Gmail & more to save recall time15:19 – Probing reflection questions vs. copy-paste AI output19:02 – Over 1,000 unique runs: thousands of hours saved in one cycle19:27 – Stakeholder feedback agent explained21:21 – Shifting from recall to reflection and effectiveness23:50 – Demo: Executive account summary agent for customer insights27:55 – Scaling AI internally: AI labs, Genius Bars & Slack communities31:00 – Why AI is enhancing—not killing—creativity32:07 – Notebook LM demo: from docs to enablement videos in seconds35:27 – How weekly “snippets” create accountability and unblock teams36:00 – Agents growing faster than employees—future of work projections38:05 – Scaling adoption with big, relevant use cases39:09 – Maddie’s outlook: building comfort with experimentation and collaborationTools & Technologies MentionedGlean – AI-powered enterprise search and agentic workflow builder, securely connected to company data sources.Notebook LM – Google’s AI notebook that now generates enablement videos instantly from documents.Salesforce, Slack, Google Drive, Gmail, Confluence – Data sources integrated into Motive’s AI agents for recall and analysis.Subscribe at⁠ thisnewway.com⁠ to get the step-by-step playbooks, tools, and workflows.

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