FoDES - Future of Design & Engineering Software

We talk with OpenSpace CTO Michael Fleischman about turning job-site photos into spatial data that teams can actually act on, from 360 degree capture to progress tracking and AI agents. We dig into why construction software adoption is so hard, and what changes when your phone can be used to create higher-quality data and automation. 
• Michael’s path from philosophy and psychology to computational linguistics and AI 
• Meeting OpenSpace co-founders at MIT Media Lab and pivoting into construction 
• Reality capture as the foundation and why “agents need eyes” 
• Cameras vs LiDAR on phones and why photos solve most field needs 
• AI autolocation as indoor GPS without beacons 
• Lowering friction as the real key to construction tech adoption 
• Progress tracking against BIM models or 2D drawings and closing the loop with reality 
• Disperse acquisition and why construction-specific spatial understanding matters 
• Flagging potential issues with Spotlight and keeping humans in control 
• Letting customers build customized agents for safety, QA, and workflows 

Matt McElvogue, VP at Teague, talks about Teague's human-centered design. We explore how building early aligns design, engineering, and business, and why full-scale prototypes beat slide decks. From accessible aircraft cabins to friendlier autonomous shuttles, we show how human-centered design meets hard constraints while accounting for many factors, such as aesthetics and functionality, that design engineers may not consider.

• Teague’s “thinking through making” philosophy across aerospace, automotive and defense
• Tooling choices from Rhino and SolisWorks to CATIA for aerospace rigor
• Full-scale cabin mockups and high-fidelity showpieces that survive travel
• Aligning desirability with feasibility in regulated environments
• Accessibility in aviation using sensors and smart wayfinding
• Factory-floor innovation with a microphone-based wire seating tool
• Where Teague complements in‑house prototype shops
• Autonomy, safety, public trust and external vehicle communication
• A friendly, bidirectional autonomous school shuttle concept
• Faster visualization, humanoid robots and emergent AI-driven design

We talk with Makistry founder Parth Meta about turning plain English prompts into parametric CAD and why a structured AI “brainstorm” can speed design without losing engineering control. We dig into standards-aware reasoning, exports, limitations, and the roadmap for assemblies and 2D-to-3D.

• Why CAD still slows real projects
• Text to parametric models through a guided brainstorm
• Using RAG to ground standards like M4 and hole specs
• Open Cascade kernel, STEP exports, in-browser visualization
• Measuring and parameter checks for trust and repeatability
• Limits on complexity and plans for sketches to 3D
• Assemblies, mates, and constraints on the roadmap
• Moving beyond copilots to AI-native design and CAM
• Balancing startup work with school and sport
• Making geometry organic yet manufacturable

We trace how focused simulation wins over all-in-one platforms, then try to find out more about the design of an Olympic helmet  — with no luck. Rand Simulation experts use LS-DYNA and validate the results to cut risk and time. We close with a frank take on what AI can and cannot do for complex physics and where humans must stay in the loop.

• ANSYS ability to simulate crash behaviour, fragmentation
• GPU solvers move design feedback to seconds
• How designers and analysts collaborate without overlap
• Services, training, and keeping skills sharp
• Aerodynamic shell vs impact liner complexity
• LS-DYNA for explicit dynamics and complex foams
• DOEs to find worst cases across speed and temperature
• 3D-printed lattices promise and current limits
• Safety trade-offs comfort, mass, and adoption
• Where AI assists setup vs where experts decide

Amit Shastri, CTO Americas at Digitate, explains how composite AI moves operations from reactive firefighting to predictive and autonomous action, without sidelining human judgment or ripping out trusted systems. Digitate’s approach blends logical reasoning, LLMs, and guardrails to deliver unified observability across IT, OT, and business processes.

• Regional CTO role bridging customers and product
• Autonomous and ticketless operations as the North Star
• Predictive alerts that prevent downtime
• Horizontal observability across procure to pay
• Integrations with ITSM, monitoring, and CMDB
• Composite AI with logic, LLMs, and human approvals
• Action firewalls and role-based controls for safety
• Job shifts from doers to exception handlers
• Build vs buy tradeoffs and enterprise scale
• Natural language interfaces over complex tools
• Leveraging legacy systems for rich operational data
• AI’s global landscape and India’s momentum

We talk with Lukas Fraser, VP of Product at Looq AI, about a camera-first platform that delivers survey-grade 3D models and automates utility workflows. We cover hardware design, accuracy claims, pole and cable analysis (for power lines), and why controlled capture makes photogrammetry competitive with LiDAR.

• Controlled handheld capture with four synchronized lenses and GNSS
• Calibrated hardware and encrypted storage with cloud processing
• Point clouds, panos, and ground-view outputs for engineers
• One-centimeter relative measurements for pole loading analysis
• Image-based detection projected to 3D for faster extraction
• Complementary roles of photogrammetry and LiDAR
• Subscription pricing with hardware, processing, and updates
• Integrations with existing survey and utility software
• Change detection to update models without resurveying

We talk to Tudor Vasiliu, founder and director of Panoptikon, about how architects use AI to elevate visualization without losing control, unpacking “AI passes,” professional guardrails, and why speed still needs expertise. A live demo shows rapid mood and lighting iteration, while we call for better client tools and more usable AEC software.

• AI passes that enhance materials, lighting, foliage, and people
• Why expert workflows beat one‑prompt myths
• Accuracy and ethics in public review visuals
• Faster iteration with in‑house tools and cloud models
• Video enhancements from stills and CG using diffusion
• Client expectations for immersive, truthful previews
• Bridging 2D habits to BIM and lightweight planning
• Startups’ agility vs software giants’ slow pace
• Natural interfaces as the next AEC breakthrough
• Guardrails to keep framing, dimensions, and intent intact

We talk with CTO and co-founder Theopile Allard about Neural Concept’s AI copilot for engineering and how option-driven workflows change speed, creativity, and trust in simulation-heavy design. We explore physics prediction, geometry generation, LLM agents, and how legacy solvers stay central.

• AI copilot that creates and evaluates many variants
• Physics predictive engine for CFD, structures, EM
• Geometry generation to expand design spaces
• LLM agents linking rules, docs, and constraints
• Solver integration and uncertainty triggers
• Fluids as a high-impact domain for discovery
• Real-world examples including quieter impellers
• Iterative, interactive design with plain English
• Training, boot camps, and community kit
• Scaling through PLM and enterprise systems
• Human-first approach to protect jobs and skills

We talk with Arjun and Kanal Jain, co-founders of Tandem about building an AI knowledge layer that captures design decisions, links requirements to CAD, and helps engineers spend more time designing. We compare text-to-CAD promises to enterprise reality, dig into traceability and DFM, and explore how integrations unlock better simulation.

• Capturing design intent across CAD, PDM, PLM
• Linking requirements, tests, and design changes
• Closing the manufacturing feedback loop
• Reducing rework and documentation overhead
• Enabling simulation through shared context
• Funding path, pilots, and early customers
• Differentiation from text-to-CAD and new CAD software
• Partner strategy with incumbents and AI tools

We trace FIU’s early bet on AI, the rise of AI-ready engineering education, and why security research must outpace attackers. From LLM jailbreaks to drone resilience, we share how to validate tools, keep fundamentals strong, and deploy AI safely in the real world.

• FIU’s AI strategy across engineering disciplines
• Faculty journey from cybersecurity to AI-driven defense
• Research strength, funding, and emerging tech focus
• AI Summit takeaways from flood modeling to controls
• Quantum threats and post-quantum cryptography
• LLM jailbreak risks and malware generation
• Layered defense and resilience-by-design
• Teaching with AI while preserving fundamentals
• AI minor structure and discipline-specific courses
• Drone security via side-channel sensing and ML
• Adversarial ML in cyber-physical systems
• Affordability, social mobility, and ROI