<![CDATA[Sovereign Stack]]>Sovereign Stack is the antidote to the AI hype cycle. Hosted by Stéphane Boghossian, this is a twice-weekly briefing at the collision point of practical software engineering, legal architecture, and data sovereignty. No buzzwords, no toy demos—just what actually survives production and regulatory scrutiny.

Every episode cuts straight to the ground truth:

  • The Slop of the Week: Ruthlessly dismantling an overhyped headline, synthetic benchmark, or vaporware launch.
  • The Reality Check: Candid breakdowns of multi-jurisdiction data routing, governance frameworks, and real enterprise AI deployments.
  • The Operational Takeaway: Hard-won rules for what works today in engineering and compliance.

Two formats every week:

  • Tuesdays: Unfiltered deep dives with the engineers, legal tacticians, and operators building sovereign infrastructure.
  • Thursdays: High-conviction, bite-sized host teardowns of breaking regulatory shifts and technical papers.

25 minutes. Zero noise. Built for builders, counsel, and operators who value signal over slop.

]]>https://haqq.ai/Riverside.fm (https://riverside.com)Fri, 30 Oct 2026 20:32:51 GMTSat, 24 Oct 2026 09:32:23 GMT60Stephane Boghossian<p><b><strong>Sovereign Stack</strong></b> is the antidote to the AI hype cycle. Hosted by Stéphane Boghossian, this is a twice-weekly briefing at the collision point of practical software engineering, legal architecture, and data sovereignty. No buzzwords, no toy demos—just what actually survives production and regulatory scrutiny.</p><p>Every episode cuts straight to the ground truth:</p><ul><li><b><strong>The Slop of the Week:</strong></b> Ruthlessly dismantling an overhyped headline, synthetic benchmark, or vaporware launch.</li><li><b><strong>The Reality Check:</strong></b> Candid breakdowns of multi-jurisdiction data routing, governance frameworks, and real enterprise AI deployments.</li><li><b><strong>The Operational Takeaway:</strong></b> Hard-won rules for what works today in engineering and compliance.</li></ul><p>Two formats every week:</p><ul><li><b><strong>Tuesdays:</strong></b> Unfiltered deep dives with the engineers, legal tacticians, and operators building sovereign infrastructure.</li><li><b><strong>Thursdays:</strong></b> High-conviction, bite-sized host teardowns of breaking regulatory shifts and technical papers.</li></ul><p>25 minutes. Zero noise. Built for builders, counsel, and operators who value signal over slop.</p>episodicStephane Boghossianstephanemboghossian@gmail.comno<![CDATA[Code to Video: Making Consistent AI Content With Hyperframes and Higgsfield]]>Stephane talks with Nicolas, community manager at HAQQ, who taught himself AI video production without a video background. They explain the process behind the AI videos HAQQ now publishes. Their goal is to avoid the generic, one-shot look people call "AI slop."

What they cover:

  • Why code-to-video is taking off: Large language models are good at writing code, so they can turn plain-English ideas into animated, watchable video.
  • Hyperframes vs. Higgsfield: Hyperframes works as the editor that sequences and animates. Higgsfield generates the assets, routing to different models for images, audio and video. They work together rather than compete.
  • The Picker: A review page where the team chooses between AI-generated versions of each frame. It lets them check consistency before spending time on a full render.
    1. Their playbook:
    2. Start with a story.
    3. Plan a frame-by-frame version.
    4. Generate cheap static images first.
    5. Turn those into GIFs.
    6. Build the full video with transitions.
    7. Add music and edit.
  • Better prompts: They write detailed prompts in a task manager, covering story, characters, colors and style, instead of sending a raw idea.
  • Testing before posting: They try content as Instagram trial reels, then post the winners on other platforms.
  • Humans and tools: Taste, storytelling and direction still need a person. Motion graphics tools like After Effects are increasingly replaceable with code.

Their advice: build your taste by consuming good content, keep a person in the loop at every step, and focus on quality, speed and consistency.

]]>https://www.instagram.com/haqq.ai/965c13a3-167f-4760-80c0-9acd2c9f17a3Fri, 30 Oct 2026 06:30:00 GMT<p>Stephane talks with Nicolas, community manager at HAQQ, who taught himself AI video production without a video background. They explain the process behind the AI videos HAQQ now publishes. Their goal is to avoid the generic, one-shot look people call "AI slop."</p><p>What they cover:</p><ul><li><b><strong>Why code-to-video is taking off:</strong></b> Large language models are good at writing code, so they can turn plain-English ideas into animated, watchable video.</li><li><b><strong>Hyperframes vs. Higgsfield:</strong></b> Hyperframes works as the editor that sequences and animates. Higgsfield generates the assets, routing to different models for images, audio and video. They work together rather than compete.</li><li><b><strong>The Picker:</strong></b> A review page where the team chooses between AI-generated versions of each frame. It lets them check consistency before spending time on a full render.<ol><li><b><strong>Their playbook:</strong></b></li><li>Start with a story.</li><li>Plan a frame-by-frame version.</li><li>Generate cheap static images first.</li><li>Turn those into GIFs.</li><li>Build the full video with transitions.</li><li>Add music and edit.</li></ol></li><li><b><strong>Better prompts:</strong></b> They write detailed prompts in a task manager, covering story, characters, colors and style, instead of sending a raw idea.</li><li><b><strong>Testing before posting:</strong></b> They try content as Instagram trial reels, then post the winners on other platforms.</li><li><b><strong>Humans and tools:</strong></b> Taste, storytelling and direction still need a person. Motion graphics tools like After Effects are increasingly replaceable with code.</li></ul><p>Their advice: build your taste by consuming good content, keep a person in the loop at every step, and focus on quality, speed and consistency.</p>no00:28:18Code to Video: Making Consistent AI Content With Hyperframes and Higgsfieldfull<![CDATA[Solo Session: Building a Personal AI Operating System With Claude]]>In his first solo episode of the Sovereign Stack Podcast, host Stephane Boghossian shares his screen and walks through how he works with AI day to day. The setup centers on Claude Projects, Claude Code and artifacts, plus Aleph, the system he built to hold his knowledge base and automations.

What I cover:

  • Projects and workflow: How he splits his work into projects and threads. He sends ideas, notes and Instagram links to the right project at night, then reviews the finished artifacts and tasks in the morning.
  • Artifacts as a learning tool: Interactive graphs and visual explainers he built to understand topics like the Anthropic IPO and frontier models. He also made a full hardware and GPU course with a 100-question exam.
  • His "second brain": A knowledge graph built from his meeting transcripts and AI sessions. It lives on his own machine and in a private repository.
  • Work artifacts: A centralized sales materials hub with PDFs in Arabic and English, a legal taxonomy, a database of Lebanon's history, and redesigns of the product onboarding and chat.
  • Daily rituals: An 8 AM briefing that tracks news, stocks and competitors, plus an AI trends explorer. It maps 51 clusters, 301 micro trends and 27 sources.
  • Human in the loop: He reviews and approves what the system produces and checks its claims before anything ships.

His message is that you don't need to copy his setup. Build your own system, because the people going this deep into automation and AI agents are about 2% of the population, and this show is for everyone else.

]]>https://stephane.bio/10917164-b618-4881-ade5-3b44098f37d7Thu, 29 Oct 2026 07:51:08 GMT<p>In his first solo episode of the Sovereign Stack Podcast, host Stephane Boghossian shares his screen and walks through how he works with AI day to day. The setup centers on Claude Projects, Claude Code and artifacts, plus Aleph, the system he built to hold his knowledge base and automations.</p><p><i><b><strong>What I cover:</strong></b></i></p><ul><li><b><strong>Projects and workflow:</strong></b> How he splits his work into projects and threads. He sends ideas, notes and Instagram links to the right project at night, then reviews the finished artifacts and tasks in the morning.</li><li><b><strong>Artifacts as a learning tool:</strong></b> Interactive graphs and visual explainers he built to understand topics like the Anthropic IPO and frontier models. He also made a full hardware and GPU course with a 100-question exam.</li><li><b><strong>His "second brain":</strong></b> A knowledge graph built from his meeting transcripts and AI sessions. It lives on his own machine and in a private repository.</li><li><b><strong>Work artifacts:</strong></b> A centralized sales materials hub with PDFs in Arabic and English, a legal taxonomy, a database of Lebanon's history, and redesigns of the product onboarding and chat.</li><li><b><strong>Daily rituals:</strong></b> An 8 AM briefing that tracks news, stocks and competitors, plus an AI trends explorer. It maps 51 clusters, 301 micro trends and 27 sources.</li><li><b><strong>Human in the loop:</strong></b> He reviews and approves what the system produces and checks its claims before anything ships.</li></ul><p>His message is that you don't need to copy his setup. Build your own system, because the people going this deep into automation and AI agents are about 2% of the population, and this show is for everyone else.</p>no00:32:50Solo Session: Building a Personal AI Operating System With Claudefull<![CDATA[How HAQQ's Sales Team Uses AI Without Leaking Client Data]]>In this episode of the Sovereign Stack Podcast, Stephane talks with Ronald Harfouche, VP of Sales at HAQQ. Ronald was previously a chief revenue officer across several regulated industries. They look at how a sales team can use AI when client data is sensitive.Ronald explains how the team brings in leads and turns them into meetings and customers:

  • Demo bookings go straight to a tailored demo, built around each prospect's use case.
  • Free sign-ups are scored on factors like credit usage, email type and stated profession. The best ones are exported to Apollo and placed into outreach sequences by email, phone and LinkedIn.
  • Outbound lists are built by company, location and persona, then enriched with Apollo contact data.
  • Salesforce syncs with Apollo and uses enterprise AI agents to log meeting notes and update next steps.

They also cover:

  • How AI helps sales teams quickly customise collateral, proposals and presentations with a client's logo and use case
  • Why the team keeps strict limits on what AI can connect to, to protect client emails and phone numbers
  • Where AI helps salespeople (prioritising leads, refining messaging) and where humans still matter, especially on calls and voice
]]>https://haqq.ai/0703054f-9c55-4032-8563-2dc1293ec5a0Wed, 28 Oct 2026 08:13:14 GMT<p>In this episode of the Sovereign Stack Podcast, Stephane talks with Ronald Harfouche, VP of Sales at HAQQ. Ronald was previously a chief revenue officer across several regulated industries. They look at how a sales team can use AI when client data is sensitive.Ronald explains how the team brings in leads and turns them into meetings and customers:</p><ul><li>Demo bookings go straight to a tailored demo, built around each prospect's use case.</li><li>Free sign-ups are scored on factors like credit usage, email type and stated profession. The best ones are exported to Apollo and placed into outreach sequences by email, phone and LinkedIn.</li><li>Outbound lists are built by company, location and persona, then enriched with Apollo contact data.</li><li>Salesforce syncs with Apollo and uses enterprise AI agents to log meeting notes and update next steps.</li></ul><p>They also cover:</p><ul><li>How AI helps sales teams quickly customise collateral, proposals and presentations with a client's logo and use case</li><li>Why the team keeps strict limits on what AI can connect to, to protect client emails and phone numbers</li><li>Where AI helps salespeople (prioritising leads, refining messaging) and where humans still matter, especially on calls and voice</li></ul>no00:27:18How HAQQ's Sales Team Uses AI Without Leaking Client Datafull<![CDATA[Learning AI on the Job: Filtering 100 Events Down to the Ones That Matter]]>Stephane sits down with Jean, who recently moved from operations to growth at HAQQ. They talk about how he went from using AI as a "Google++" to building his own automations.Jean has worked on more than 300 events over six years. He explains how he built an AI scoring system that rates each event out of 100 on location, timing, speakers, agenda and other factors. Out of about 100 events for 2026 and early 2027, it helped narrow the list to 4–5 events to speak at or exhibit at, and about 10 to attend.In this episode:

  • Why Jean joined HAQQ and how his role shifted from ops to growth
  • How the event scoring system works, plus a story of a two-hour trip to meet one key person
  • Why AI can recommend, but humans must make the decisions and show up
  • How to choose which repeating tasks to automate, and when to stop iterating (set clear KPIs first)
  • Why he approves each automation step instead of letting the tool run on its own
  • Stephane's 5-step framework for starting with AI:
    1. Identify the task to automate.
    2. Map the possible steps.
    3. Define the output.
    4. Gather context and research.
    5. Prepare your prompt and monitor the conversation.
  • Jean's two biggest lessons: AI helps you do things you couldn't do manually, and the time it saves lets you learn things outside your expertise
]]>https://www.haqq.ai/b811930c-16aa-4673-9362-39f7f9fdeff9Tue, 27 Oct 2026 13:44:51 GMT<p>Stephane sits down with Jean, who recently moved from operations to growth at HAQQ. They talk about how he went from using AI as a "Google++" to building his own automations.Jean has worked on more than 300 events over six years. He explains how he built an AI scoring system that rates each event out of 100 on location, timing, speakers, agenda and other factors. Out of about 100 events for 2026 and early 2027, it helped narrow the list to 4–5 events to speak at or exhibit at, and about 10 to attend.In this episode:</p><ul><li>Why Jean joined HAQQ and how his role shifted from ops to growth</li><li>How the event scoring system works, plus a story of a two-hour trip to meet one key person</li><li>Why AI can recommend, but humans must make the decisions and show up</li><li>How to choose which repeating tasks to automate, and when to stop iterating (set clear KPIs first)</li><li>Why he approves each automation step instead of letting the tool run on its own</li><li>Stephane's 5-step framework for starting with AI:<ol><li>Identify the task to automate.</li><li>Map the possible steps.</li><li>Define the output.</li><li>Gather context and research.</li><li>Prepare your prompt and monitor the conversation.</li></ol></li><li>Jean's two biggest lessons: AI helps you do things you couldn't do manually, and the time it saves lets you learn things outside your expertise</li></ul>no00:19:48Learning AI on the Job: Filtering 100 Events Down to the Ones That Matterfull